SIMPLE ASSEMBLY LINE BALANCING
|
|
- Toby Knight
- 5 years ago
- Views:
Transcription
1 A R C H I V E S O F M E C H A N I C A L T E C H N O L O G Y A N D A U T O M A T I O N Vol. 33 no JAN UREK, MAREK PASTWA, MARCIN WINIEWSKI SIMPLE ASSEMBLY LINE BALANCING Assembly line balancing is one of the challenges that appear when technological process of an assembly is being developed. It is a particularly difficult, computably complex task, belonging to the NP-complete class. Apart from the task mentioned above, this group includes a number of key computational problems. Due to the practical value of these complexities, as well as great cost reductions related to their optimisation, precise algorithms are being constantly investigated for them. These tasks include scheduling, compaction, permutation, sequencing, etc. What is vital, effectively developed algorithms for resolving one of the NP problems are easy to be implemented into another ones, which makes the assembly line balancing universal. The article describes balancing of an assembly line pictured as graphs. Basic concepts and important assumptions were discussed, including the restrictions and types of simple straight assembly line balancing. Key words: straight assembly line balancing, types of simple assembly line balancing 1. ASSEMBLY LINE BALANCING IN THE FORM OF A GRAPH Assembly line balancing is, to some extent, mapped out in the graph of sequence restrictions G = {V, A, t} known as the graph of precedence [1, 8]. It is a directed graph (digraph). It consists of a nonempty V = {1,..., n} set of vertices representing the operations and a finite family of arcs (edges) A = {(i, ) iv and F i }, where F i represents a set of operations directly following the I one. Each of the vertices is assigned with a t value standing for the operation time. An i operation preceding a operation is called the operation predecessor, while an i operation that can be performed subsequently to a one is known as its successor. The relationship between i and operations is called direct when there is an (i, ) arc or a (, i) one. The graph vertices relating to the operations without predecessors are called source vertices, while the ones referring to the Prof. dr hab. in. Institute of Mechanical Technology, Poznan University of Technology. Mgr in. Dr in. Sparta sp. z o.o.
2 62 J. urek, M. Pastwa, M. Winiewski operations without successors are known as sink vertices. If each of the (i, ) arcs is replaced by the (, i) in graph G, a G r reversed precedence graph is obtained. In the latter graph, preceding operations become successors, successors turn into predecessors, sources come to be sinks and sinks become sources. A sequence restrictions graph is an acyclic one, which means it does not contain any closed paths, as well as a simple graph, which makes it a digraph without any repetitive edges or loops, that is multiple (i, ) edges and (i, i) arcs [2]. A G * = (V, A *, t) subgraph can be distinguished within the G graph. The subgraph mentioned contains (i, ) arcs for each i and operation connected by a path within the G graph, that is A * = {(i, ) iv and F * i}, where F * i represents all operations (graph s nodes) following the i operation, the successors of i. The A * set contains all the arcs representing the relationships following the i operation, and the A A * set subtraction is a set of arcs corresponding to the relationships preceding the i operation. Framework for assembly line balancing is consisted in dividing the V = {1,..., n} set which assigns every operation to a S k set for k = 1,..., m, where m is the number of stations. This assignment needs to meet certain requirements. The first condition is that each operation has to be assigned to exactly one station, while the second one dictates keeping the sequence that stems from the sequence restrictions graph, which makes it indispensable to meet the following condition: if is o and S p, then for each arc (i, ) A po. The division mentioned should also meet the condition of the total t(s k ) time needed for an operation assigned to a given station to be less than or equal to given c line takt time. 2. AN EXAMPLE OF ASSEMBLY LINE BALANCING A basic assembly line balancing, known as SALB, is simplified in a number of ways, which makes it easy during the tests, yet most often different from the methods used in industrial practice. Basic conditions of this method are: assemblage of homogenous products, known, unvariable duration time of particular operations, restrictions to operation grouping expressed only in a form of a precedence graph, determined and constant line production rate, serial configuration of the assembly line, with the stations located on one side, independent and equally equipped stations. In its basic form, that is when no additional conditions are formulated, assembly line balancing narrows down to a decision problem [5, 9], concerning the
3 Simple assembly line balancing 63 question whether the operations are assigned to a given number of stations and pointing out that assignment. Figure 1 maps out a sequence restrictions graph for an exemplary Jackson s task. Particular operations are indicated by nodes, while the arcs reflect the precedence relationships among them. The task consists of 11 operations, whose total production time equals 46 units, the maximum time needed for performing one operation is 7 units and the minimum is 1 unit. The value of a given line s production rate determines its theoretical efficiency (a product leaves the line every cycle). If the production rate is stated to be 14 units and the unit equals one minute, the production rate is 60/14 products per hour, which means there are over 34 products per an 8-hour shift, while the minimum number of stations is 4 {{1, 2, 3, 5}, {6, 8, 10}, {4, 7}, {9, 11}}. It is easy to notice that the load of Station 2 is 13 units, of Station 3 10 units and of Station 4 only 9 units, in the operation division proposed. 2/2 6/2 8/6 10/5 1/6 3/5 7/3 9/5 11/4 4/7 4/10 5/1 number of operations working time Figure 1. Sequence restrictions graph for the Jackson s task If the demand for products raises to 40 per shift, the line production rate has to be decreased to 12 per unit, however, increasing the number of stations is not necessary. The division of operations among 4 stations, with a maximum load on one of them being 12 units is: {{1, 2, 5, 6},{3, 4},{8, 10},{7, 9, 11}}. The line s takt time, equalling 12 units of time, is at the same time the smallest one that allows for dividing the operations among 4 stations. A takt time that consists of 11 units requires increasing the number of stations.
4 64 J. urek, M. Pastwa, M. Winiewski 3. RESTRICTIONS IN ASSEMBLY LINE BALANCING Restrictions referring to the sequence of operations may be pictured by means of a sequence restrictions graph. As it can be observed, these restrictions may be used to determine the earliest station: E and the last one: L on which a given operation can be performed (it can be performed as early as the operations directly and indirectly preceding it are assigned), when the line production rate is determined and the number of stations is maximum. Therefore, the earliest station where a given operation can be performed is, in other words, the quotient of the total of the operation times (of the given operation, as well as its direct and indirect predecessors) and the line production rate determined. The value obtained should be rounded to the smallest integer greater or equalling it (the socalled ceiling). If the total number of the line stations is known, the last station where a given operation has to be performed can be easily determined. To indicate it, one makes an assumption that all the operations directly and indirectly following the given one have to be performed on the station where this operation takes place, or on one of the next ones. The value obtained needs to be rounded in the same way the previous one is. These relationships can be expressed by the following formulas: L E t h c * P t h for = 1,..., n (1) t th * hf m 1 c for = 1,..., n (2) where: E the earliest permissible station for a operation, L the last permissible station for a operation, m number of stations, c line takt time, t, t h and h operation times, respectively, P * operation s direct and indirect predecessors, F * operation s direct and indirect successors.
5 Simple assembly line balancing 65 The earliest and latest stations for the Jackson s task Table 1 E L SI The sequence restrictions adopted allow for stating the station interval where a certain operation has to be performed. This interval, written SI, is defined by the earliest and the last station a particular operation might be performed on: SI = = [E, L ]. By this, B k operation sets are obtained and subsequently may be potentially assigned to particular stations: B k k SI for k = 1,..., m (3) Table 1 presents the results of the Jackson s task discussed above, with the takt time equalling 14 units and the division consisting 4 stations. Basing on the data provided, sets of operations that can be assigned to particular stations are: B 1 ={1, 2, 3, 4, 5, 6}, B 2 ={2, 3, 4, 5, 6, 7, 8, 9, 10}, B 3 ={2, 3, 4, 5, 6, 7, 8, 9, 10}, B 4 ={7, 9, 10, 11}. What is vital, the station intervals stem only from the sequence restrictions, without other indispensable conditions for the solution to be acceptable. 4. TYPES OF SIMPLE ASSEMBLY LINE BALANCING Depending on the product, assembly line balancing can be in formof one of the three types of tasks described below: 1) SALBP-1 [4] minimisation of the m number of stations at a given production rate c: min{m (m, c) is feasible for a given c production rate}, 2) SALBP-2 [3] minimisation of the c line production rate with a given number of stations: {c (m, c) is feasible for the m number of stations}, 3) SALBP-E maximisation of the E line effectiveness, that is minimisation of the product of m c, max{ t sum /(m c) (m, c) is feasible for possible m and c vaues}.
6 66 J. urek, M. Pastwa, M. Winiewski The SALBP-1 and SALBP-2 tasks are similar. It can be observed that the constant c line production rate parameter in SALBP-1 undergoes minimisation in SALBP-2 and vice versa. The invariable m number of stations in SALBP-2 is, in turn, minimised in SALBP-1, which makes these two tasks mutually complementary. A suboptimal solution (that is, dividing into the lowest possible number of stations), found under the criterion of line stations minimisation, can be improved by minimising the line production rate. In this case the number of stations is invariable. Due to such steps taken, the effectiveness of an assembly line may be improved, which makes it resemble SALBP-E. The criterion is the best assembly line effectiveness when m and c numbers of stations are determined at particular intervals and a given c production rate. 5. CONCLUSION As literature [19] shows, assembly line production rate minimisation for a given number of stations always leads to a decreased total of idle times. Reducing the production rate, and at the same time minimising the number of stations, makes the idle times increase. Therefore, stating which changes of the stations number and the line production rate (m and c) are acceptable is crucial for the quality of the derived solutions. However, it is uneasy, as no guidelines are known before the solution appears. SALBP-1 and SALBP-E are mostly often used in the design of new assembly lines in the industrial practice, and their structure and required productivity value can be fully determined. SALBP-2 is, in turn, used in order to improve the effectiveness of existing assembly lines, as well as when there is a need for redesigning them to a limited extent. What is vital, though seemingly similar, the assembly line balancing SALBP-1 and SALBP-2 types require different methods and algorithms. REFERENCES [1] Ciszak O., urek J., Wyznaczanie kolenoci montau czci i zespoów maszyn, Archiwum Technologii Maszyn i Automatyzaci, 1998, vol. 18, nr 2. [2] Cormen T.H., Leiserson C.E., Rivest R.L., Introduction to algorithms, Warszawa, WNT [3] Nearchou A.C., Balancing large assembly lines by a new heuristic based on differential evolution method, International Journal of Advanced Manufacturing Technology, 2007, vol. 34, issue 9 10, p [4] Pastor R., Ferrer L., An improved mathematical program to solve the simple assembly line balancing problem, International Journal of Production Research, 2009, vol. 47, issue 11, p
7 Simple assembly line balancing 67 [5] Pastwa M., Balansowanie linii montaowe za pomoc algorytmów ewolucynych, Ph.D. thesis, Poznan University of Technology [6] urek J., Algorytmizaca balansowania linii montaowe, Archiwum Technologii Budowy Maszyn, 1992, vol. 10. [7] urek J., Technologia montau, Zeszyty Naukowe Politechniki Poznaskie, Mechanika, 1994, nr 39. [8] urek J., Ciszak O., Modelowanie oraz symulaca kolenoci montau czci i zespoów maszyn za pomoc teorii grafów, Pozna, Wydawnictwo Politechniki Poznaskie [9] urek J., Pastwa M., Próba zastosowania algorytmu genetycznego do balansowania linii montaowe, in: Technika i technologia montau maszyn. IV International Science and Technology Conference Materials, Rzeszów ZADANIE BALANSOWANIA PROSTEJ LINII MONTAOWEJ S t r e s z c z e n i e W artykule opisano zagadnienia dotyczce balansowania linii montaowe przedstawione za pomoc grafów. Okrelono podstawowe pocia, omówiono niezbdne zaoenia, w tym ograniczenia oraz odmiany prostego zadania balansowania proste linii montaowe. Sowa kluczowe: balansowanie linii montaowe proste, odmiany prostego zadania balansowania linii montaowe
physicsandmathstutor.com
ADVANCED GCE MATHEMATICS 4737 Decision Mathematics 2 Candidates answer on the answer booklet. OCR supplied materials: 8 page answer booklet (sent with general stationery) Insert for Questions 4 and 6 (inserted)
More informationWe are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists. International authors and editors
We are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists 3,500 108,000 1.7 M Open access books available International authors and editors Downloads Our
More informationLL assigns tasks to stations and decides on the position of the stations and conveyors.
2 Design Approaches 2.1 Introduction Designing of manufacturing systems involves the design of products, processes and plant layout before physical construction [35]. CE, which is known as simultaneous
More informationDyck paths, standard Young tableaux, and pattern avoiding permutations
PU. M. A. Vol. 21 (2010), No.2, pp. 265 284 Dyck paths, standard Young tableaux, and pattern avoiding permutations Hilmar Haukur Gudmundsson The Mathematics Institute Reykjavik University Iceland e-mail:
More informationOn uniquely k-determined permutations
On uniquely k-determined permutations Sergey Avgustinovich and Sergey Kitaev 16th March 2007 Abstract Motivated by a new point of view to study occurrences of consecutive patterns in permutations, we introduce
More informationAMORE meeting, 1-4 October, Leiden, Holland
A graph theoretical approach to shunting problems L. Koci, G. Di Stefano Dipartimento di Ingegneria Elettrica, Università dell Aquila, Italy AMORE meeting, 1-4 October, Leiden, Holland Train depot algorithms
More informationScheduling. Radek Mařík. April 28, 2015 FEE CTU, K Radek Mařík Scheduling April 28, / 48
Scheduling Radek Mařík FEE CTU, K13132 April 28, 2015 Radek Mařík (marikr@fel.cvut.cz) Scheduling April 28, 2015 1 / 48 Outline 1 Introduction to Scheduling Methodology Overview 2 Classification of Scheduling
More informationA slope of a line is the ratio between the change in a vertical distance (rise) to the change in a horizontal
The Slope of a Line (2.2) Find the slope of a line given two points on the line (Objective #1) A slope of a line is the ratio between the change in a vertical distance (rise) to the change in a horizontal
More informationA GRAPH THEORETICAL APPROACH TO SOLVING SCRAMBLE SQUARES PUZZLES. 1. Introduction
GRPH THEORETICL PPROCH TO SOLVING SCRMLE SQURES PUZZLES SRH MSON ND MLI ZHNG bstract. Scramble Squares puzzle is made up of nine square pieces such that each edge of each piece contains half of an image.
More informationCOMP9414: Artificial Intelligence Problem Solving and Search
CMP944, Monday March, 0 Problem Solving and Search CMP944: Artificial Intelligence Problem Solving and Search Motivating Example You are in Romania on holiday, in Arad, and need to get to Bucharest. What
More informationProject Planning and Scheduling
Chapter 6, Section Project Planning and Scheduling 1 Learning Outcome Apply engineering management principles and tools (e.g., Gantt charts, CPM) to the planning and management of work systems engineering
More informationCS100: DISCRETE STRUCTURES. Lecture 8 Counting - CH6
CS100: DISCRETE STRUCTURES Lecture 8 Counting - CH6 Lecture Overview 2 6.1 The Basics of Counting: THE PRODUCT RULE THE SUM RULE THE SUBTRACTION RULE THE DIVISION RULE 6.2 The Pigeonhole Principle. 6.3
More information12. 6 jokes are minimal.
Pigeonhole Principle Pigeonhole Principle: When you organize n things into k categories, one of the categories has at least n/k things in it. Proof: If each category had fewer than n/k things in it then
More informationTopics to be covered
Basic Counting 1 Topics to be covered Sum rule, product rule, generalized product rule Permutations, combinations Binomial coefficients, combinatorial proof Inclusion-exclusion principle Pigeon Hole Principle
More informationRouting Messages in a Network
Routing Messages in a Network Reference : J. Leung, T. Tam and G. Young, 'On-Line Routing of Real-Time Messages,' Journal of Parallel and Distributed Computing, 34, pp. 211-217, 1996. J. Leung, T. Tam,
More informationRelay Placement in Sensor Networks
Relay Placement in Sensor Networks Jukka Suomela 14 October 2005 Contents: Wireless Sensor Networks? Relay Placement? Problem Classes Computational Complexity Approximation Algorithms HIIT BRU, Adaptive
More informationThe Pigeonhole Principle
The Pigeonhole Principle Some Questions Does there have to be two trees on Earth with the same number of leaves? How large of a set of distinct integers between 1 and 200 is needed to assure that two numbers
More informationGraphs of Tilings. Patrick Callahan, University of California Office of the President, Oakland, CA
Graphs of Tilings Patrick Callahan, University of California Office of the President, Oakland, CA Phyllis Chinn, Department of Mathematics Humboldt State University, Arcata, CA Silvia Heubach, Department
More informationThe Problem. Tom Davis December 19, 2016
The 1 2 3 4 Problem Tom Davis tomrdavis@earthlink.net http://www.geometer.org/mathcircles December 19, 2016 Abstract The first paragraph in the main part of this article poses a problem that can be approached
More informationEFFECTIVE CHANNEL CODING OF SERIALLY CONCATENATED ENCODERS AND CPM OVER AWGN AND RICIAN CHANNELS
EFFECTIVE CHANNEL CODING OF SERIALLY CONCATENATED ENCODERS AND CPM OVER AWGN AND RICIAN CHANNELS Manjeet Singh (ms308@eng.cam.ac.uk) Ian J. Wassell (ijw24@eng.cam.ac.uk) Laboratory for Communications Engineering
More informationDecision Mathematics D1 Advanced/Advanced Subsidiary. Friday 17 May 2013 Morning Time: 1 hour 30 minutes
Paper Reference(s) 6689/01R Edexcel GCE Decision Mathematics D1 Advanced/Advanced Subsidiary Friday 17 May 2013 Morning Time: 1 hour 30 minutes Materials required for examination Nil Items included with
More informationPermutation graphs an introduction
Permutation graphs an introduction Ioan Todinca LIFO - Université d Orléans Algorithms and permutations, february / Permutation graphs Optimisation algorithms use, as input, the intersection model (realizer)
More information2 person perfect information
Why Study Games? Games offer: Intellectual Engagement Abstraction Representability Performance Measure Not all games are suitable for AI research. We will restrict ourselves to 2 person perfect information
More informationLower Bounds for the Number of Bends in Three-Dimensional Orthogonal Graph Drawings
ÂÓÙÖÒÐ Ó ÖÔ ÐÓÖØÑ Ò ÔÔÐØÓÒ ØØÔ»»ÛÛÛº ºÖÓÛÒºÙ»ÔÙÐØÓÒ»» vol.?, no.?, pp. 1 44 (????) Lower Bounds for the Number of Bends in Three-Dimensional Orthogonal Graph Drawings David R. Wood School of Computer Science
More informationA NUMBER THEORY APPROACH TO PROBLEM REPRESENTATION AND SOLUTION
Session 22 General Problem Solving A NUMBER THEORY APPROACH TO PROBLEM REPRESENTATION AND SOLUTION Stewart N, T. Shen Edward R. Jones Virginia Polytechnic Institute and State University Abstract A number
More informationParallel tap-changer controllers under varying load conditions (Part 1)
Parallel tap-changer controllers under varying load conditions (Part 1) by Prof. B S Rigby, T Modisane, University of KwaZulu-Natal This paper investigates the performance of voltage regulating relays
More informationPractical Application of Two-Way Multiple Overlapping Relationships in a BDM Network
Journal of Civil Engineering and Architecture 10 (2016) 1318-1328 doi: 10.17265/1934-7359/2016.12.003 D DAVID PUBLISHING Practical Application of Two-Way Multiple Overlapping Relationships in a BDM Network
More informationMASSACHUSETTS INSTITUTE OF TECHNOLOGY
MASSACHUSETTS INSTITUTE OF TECHNOLOGY 15.053 Optimization Methods in Management Science (Spring 2007) Problem Set 7 Due April 12 th, 2007 at :30 pm. You will need 157 points out of 185 to receive a grade
More informationA tournament problem
Discrete Mathematics 263 (2003) 281 288 www.elsevier.com/locate/disc Note A tournament problem M.H. Eggar Department of Mathematics and Statistics, University of Edinburgh, JCMB, KB, Mayeld Road, Edinburgh
More informationFormalising Event Reconstruction in Digital Investigations
Formalising Event Reconstruction in Digital Investigations Pavel Gladyshev The thesis is submitted to University College Dublin for the degree of PhD in the Faculty of Science August 2004 Department of
More informationMath 1111 Math Exam Study Guide
Math 1111 Math Exam Study Guide The math exam will cover the mathematical concepts and techniques we ve explored this semester. The exam will not involve any codebreaking, although some questions on the
More informationThe study of probability is concerned with the likelihood of events occurring. Many situations can be analyzed using a simplified model of probability
The study of probability is concerned with the likelihood of events occurring Like combinatorics, the origins of probability theory can be traced back to the study of gambling games Still a popular branch
More informationChapter 12. Cross-Layer Optimization for Multi- Hop Cognitive Radio Networks
Chapter 12 Cross-Layer Optimization for Multi- Hop Cognitive Radio Networks 1 Outline CR network (CRN) properties Mathematical models at multiple layers Case study 2 Traditional Radio vs CR Traditional
More informationSolving Assembly Line Balancing Problem using Genetic Algorithm with Heuristics- Treated Initial Population
Solving Assembly Line Balancing Problem using Genetic Algorithm with Heuristics- Treated Initial Population 1 Kuan Eng Chong, Mohamed K. Omar, and Nooh Abu Bakar Abstract Although genetic algorithm (GA)
More informationAlgorithmique appliquée Projet UNO
Algorithmique appliquée Projet UNO Paul Dorbec, Cyril Gavoille The aim of this project is to encode a program as efficient as possible to find the best sequence of cards that can be played by a single
More information6.042/18.062J Mathematics for Computer Science December 17, 2008 Tom Leighton and Marten van Dijk. Final Exam
6.042/18.062J Mathematics for Computer Science December 17, 2008 Tom Leighton and Marten van Dijk Final Exam Problem 1. [25 points] The Final Breakdown Suppose the 6.042 final consists of: 36 true/false
More informationCMPUT 396 Tic-Tac-Toe Game
CMPUT 396 Tic-Tac-Toe Game Recall minimax: - For a game tree, we find the root minimax from leaf values - With minimax we can always determine the score and can use a bottom-up approach Why use minimax?
More informationOn uniquely k-determined permutations
Discrete Mathematics 308 (2008) 1500 1507 www.elsevier.com/locate/disc On uniquely k-determined permutations Sergey Avgustinovich a, Sergey Kitaev b a Sobolev Institute of Mathematics, Acad. Koptyug prospect
More informationSRI VENKATESWARA COLLEGE OF ENGINEERING AND TECHNOLOGY
SRI VENKATESWARA COLLEGE OF ENGINEERING AND TECHNOLOGY DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING IC 6501 CONTROL SYSTEMS UNIT I - SYSTEMS AND THEIR REPRESETNTATION` TWO MARKS QUESTIONS WITH
More informationMAT3707. Tutorial letter 202/1/2017 DISCRETE MATHEMATICS: COMBINATORICS. Semester 1. Department of Mathematical Sciences MAT3707/202/1/2017
MAT3707/0//07 Tutorial letter 0//07 DISCRETE MATHEMATICS: COMBINATORICS MAT3707 Semester Department of Mathematical Sciences SOLUTIONS TO ASSIGNMENT 0 BARCODE Define tomorrow university of south africa
More informationarxiv: v2 [cs.ai] 15 Jul 2016
SIMPLIFIED BOARDGAMES JAKUB KOWALSKI, JAKUB SUTOWICZ, AND MAREK SZYKUŁA arxiv:1606.02645v2 [cs.ai] 15 Jul 2016 Abstract. We formalize Simplified Boardgames language, which describes a subclass of arbitrary
More informationCAN for time-triggered systems
CAN for time-triggered systems Lars-Berno Fredriksson, Kvaser AB Communication protocols have traditionally been classified as time-triggered or eventtriggered. A lot of efforts have been made to develop
More informationLINEAR EQUATIONS IN TWO VARIABLES
LINEAR EQUATIONS IN TWO VARIABLES What You Should Learn Use slope to graph linear equations in two " variables. Find the slope of a line given two points on the line. Write linear equations in two variables.
More informationSolutions to Problem Set 7
Massachusetts Institute of Technology 6.4J/8.6J, Fall 5: Mathematics for Computer Science November 9 Prof. Albert R. Meyer and Prof. Ronitt Rubinfeld revised November 3, 5, 3 minutes Solutions to Problem
More informationON THE PERMUTATIONAL POWER OF TOKEN PASSING NETWORKS.
ON THE PERMUTATIONAL POWER OF TOKEN PASSING NETWORKS. M. H. ALBERT, N. RUŠKUC, AND S. LINTON Abstract. A token passing network is a directed graph with one or more specified input vertices and one or more
More information1 = 3 2 = 3 ( ) = = = 33( ) 98 = = =
Math 115 Discrete Math Final Exam December 13, 2000 Your name It is important that you show your work. 1. Use the Euclidean algorithm to solve the decanting problem for decanters of sizes 199 and 98. In
More informationUNIT 2: RATIONAL NUMBER CONCEPTS WEEK 5: Student Packet
Name Period Date UNIT 2: RATIONAL NUMBER CONCEPTS WEEK 5: Student Packet 5.1 Fractions: Parts and Wholes Identify the whole and its parts. Find and compare areas of different shapes. Identify congruent
More informationComplex DNA and Good Genes for Snakes
458 Int'l Conf. Artificial Intelligence ICAI'15 Complex DNA and Good Genes for Snakes Md. Shahnawaz Khan 1 and Walter D. Potter 2 1,2 Institute of Artificial Intelligence, University of Georgia, Athens,
More informationTHE GAME CREATION OPERATOR
2/6/17 THE GAME CREATION OPERATOR Joint work with Urban Larsson and Matthieu Dufour Silvia Heubach California State University Los Angeles SoCal-Nevada Fall 2016 Section Meeting October 22, 2016 Much of
More informationRolling Partial Rescheduling with Dual Objectives for Single Machine Subject to Disruptions 1)
Vol.32, No.5 ACTA AUTOMATICA SINICA September, 2006 Rolling Partial Rescheduling with Dual Objectives for Single Machine Subject to Disruptions 1) WANG Bing 1,2 XI Yu-Geng 2 1 (School of Information Engineering,
More informationPUZZLES ON GRAPHS: THE TOWERS OF HANOI, THE SPIN-OUT PUZZLE, AND THE COMBINATION PUZZLE
PUZZLES ON GRAPHS: THE TOWERS OF HANOI, THE SPIN-OUT PUZZLE, AND THE COMBINATION PUZZLE LINDSAY BAUN AND SONIA CHAUHAN ADVISOR: PAUL CULL OREGON STATE UNIVERSITY ABSTRACT. The Towers of Hanoi is a well
More informationPermutations and Combinations
Permutations and Combinations Introduction Permutations and combinations refer to number of ways of selecting a number of distinct objects from a set of distinct objects. Permutations are ordered selections;
More informationTIME- OPTIMAL CONVERGECAST IN SENSOR NETWORKS WITH MULTIPLE CHANNELS
TIME- OPTIMAL CONVERGECAST IN SENSOR NETWORKS WITH MULTIPLE CHANNELS A Thesis by Masaaki Takahashi Bachelor of Science, Wichita State University, 28 Submitted to the Department of Electrical Engineering
More informationMathematics. (www.tiwariacademy.com) (Chapter 7) (Permutations and Combinations) (Class XI) Exercise 7.3
Question 1: Mathematics () Exercise 7.3 How many 3-digit numbers can be formed by using the digits 1 to 9 if no digit is repeated? Answer 1: 3-digit numbers have to be formed using the digits 1 to 9. Here,
More informationCRITICAL PATH ANALYSIS (AQA)
REVIION HEE EIION MH RIIL PH NLYI (Q) he main ideas are covered in Q Edexcel MEI OR he main ideas in this topic are: rawing ctivity or Precedence Networks Performing Forward and ackward Passes and Identifying
More informationFree GK Alerts- JOIN OnlineGK to NUMBERS IMPORTANT FACTS AND FORMULA
Free GK Alerts- JOIN OnlineGK to 9870807070 1. NUMBERS IMPORTANT FACTS AND FORMULA I..Numeral : In Hindu Arabic system, we use ten symbols 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 called digits to represent any number.
More informationBRITISH COLUMBIA SECONDARY SCHOOL MATHEMATICS CONTEST, 2006 Senior Preliminary Round Problems & Solutions
BRITISH COLUMBIA SECONDARY SCHOOL MATHEMATICS CONTEST, 006 Senior Preliminary Round Problems & Solutions 1. Exactly 57.4574% of the people replied yes when asked if they used BLEU-OUT face cream. The fewest
More informationRegister Allocation by Puzzle Solving
Register Allocation by Puzzle Solving EECS 322: Compiler Construction Simone Campanoni Robby Findler 4/19/2016 Materials Research paper: Authors: Fernando Magno Quintao Pereira, Jens Palsberg Title: Register
More informationGas Pipeline Construction
Gas Pipeline Construction The figure below shows 5 pipelines under consideration by a natural gas company to move gas from its 2 fields to its 2 storage areas. The numbers on the arcs show the number of
More informationA Covering System with Minimum Modulus 42
Brigham Young University BYU ScholarsArchive All Theses and Dissertations 2014-12-01 A Covering System with Minimum Modulus 42 Tyler Owens Brigham Young University - Provo Follow this and additional works
More informationMODELLING THE STRUCTURAL BARRIER ABILITY OF WOVEN FABRICS
AUTEX Research Journal, Vol. 3, No3, September 2003 AUTEX MODELLING THE STRUCTURAL BARRIER ABILITY OF WOVEN FABRICS Janusz Szosland Technical University of Łódź Department of Textile Architecture ul. Żeromskiego
More informationIt is important that you show your work. The total value of this test is 220 points.
June 27, 2001 Your name It is important that you show your work. The total value of this test is 220 points. 1. (10 points) Use the Euclidean algorithm to solve the decanting problem for decanters of sizes
More informationUNIT-III ASYNCHRONOUS SEQUENTIAL CIRCUITS TWO MARKS 1. What are secondary variables? -present state variables in asynchronous sequential circuits 2. What are excitation variables? -next state variables
More informationA Message Scheduling Scheme for All-to-all Personalized Communication on Ethernet Switched Clusters
A Message Scheduling Scheme for All-to-all Personalized Communication on Ethernet Switched Clusters Ahmad Faraj Xin Yuan Pitch Patarasuk Department of Computer Science, Florida State University Tallahassee,
More informationAsst. Prof. Thavatchai Tayjasanant, PhD. Power System Research Lab 12 th Floor, Building 4 Tel: (02)
2145230 Aircraft Electricity and Electronics Asst. Prof. Thavatchai Tayjasanant, PhD Email: taytaycu@gmail.com aycu@g a co Power System Research Lab 12 th Floor, Building 4 Tel: (02) 218-6527 1 Chapter
More informationMath 1111 Math Exam Study Guide
Math 1111 Math Exam Study Guide The math exam will cover the mathematical concepts and techniques we ve explored this semester. The exam will not involve any codebreaking, although some questions on the
More informationNon-linear load model for the local stability studies
Krzysztof OLAK, Bartosz BRIŁOWICZ, Janusz ZAFRAN Wrocław niversity of Technology, Institute of Electrical Power Engineering () Non-linear load model for the local stability studies Abstract. This paper
More informationCOMPUTER AIDED MAINTENANCE MANAGEMENT FOR TRANSPORT TELEMATICS SYSTEMS
Technical Sciences 17(3), 2014, 293 303 COMPUTER AIDED MAINTENANCE MANAGEMENT FOR TRANSPORT TELEMATICS SYSTEMS Department of Transport Telecommunications Warsaw University of Technology Received 1 September
More informationESE535: Electronic Design Automation. Previously. Today. Precedence. Conclude. Precedence Constrained
ESE535: Electronic Design Automation Day 5: January, 013 Scheduling Variants and Approaches Penn ESE535 Spring 013 -- DeHon 1 Previously Resources aren t free Share to reduce costs Schedule operations
More informationSORTING BY REVERSALS. based on chapter 7 of Setubal, Meidanis: Introduction to Computational molecular biology
SORTING BY REVERSALS based on chapter 7 of Setubal, Meidanis: Introduction to Computational molecular biology Motivation When comparing genomes across species insertions, deletions and substitutions of
More informationSearch then involves moving from state-to-state in the problem space to find a goal (or to terminate without finding a goal).
Search Can often solve a problem using search. Two requirements to use search: Goal Formulation. Need goals to limit search and allow termination. Problem formulation. Compact representation of problem
More informationChapter 4: The Building Blocks: Binary Numbers, Boolean Logic, and Gates
Chapter 4: The Building Blocks: Binary Numbers, Boolean Logic, and Gates Objectives In this chapter, you will learn about The binary numbering system Boolean logic and gates Building computer circuits
More informationUnderstanding Mixers Terms Defined, and Measuring Performance
Understanding Mixers Terms Defined, and Measuring Performance Mixer Terms Defined Statistical Processing Applied to Mixers Today's stringent demands for precise electronic systems place a heavy burden
More informationOptimal Transceiver Scheduling in WDM/TDM Networks. Randall Berry, Member, IEEE, and Eytan Modiano, Senior Member, IEEE
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 23, NO. 8, AUGUST 2005 1479 Optimal Transceiver Scheduling in WDM/TDM Networks Randall Berry, Member, IEEE, and Eytan Modiano, Senior Member, IEEE
More informationMath236 Discrete Maths with Applications
Math236 Discrete Maths with Applications P. Ittmann UKZN, Pietermaritzburg Semester 1, 2012 Ittmann (UKZN PMB) Math236 2012 1 / 43 The Multiplication Principle Theorem Let S be a set of k-tuples (s 1,
More informationSubtraction games with expandable subtraction sets
with expandable subtraction sets Bao Ho Department of Mathematics and Statistics La Trobe University Monash University April 11, 2012 with expandable subtraction sets Outline The game of Nim Nim-values
More informationTRAFFIC SIGNAL CONTROL WITH ANT COLONY OPTIMIZATION. A Thesis presented to the Faculty of California Polytechnic State University, San Luis Obispo
TRAFFIC SIGNAL CONTROL WITH ANT COLONY OPTIMIZATION A Thesis presented to the Faculty of California Polytechnic State University, San Luis Obispo In Partial Fulfillment of the Requirements for the Degree
More informationLecture 20 November 13, 2014
6.890: Algorithmic Lower Bounds: Fun With Hardness Proofs Fall 2014 Prof. Erik Demaine Lecture 20 November 13, 2014 Scribes: Chennah Heroor 1 Overview This lecture completes our lectures on game characterization.
More informationRadical Expressions and Graph (7.1) EXAMPLE #1: EXAMPLE #2: EXAMPLE #3: Find roots of numbers (Objective #1) Figure #1:
Radical Expressions and Graph (7.1) Find roots of numbers EXAMPLE #1: Figure #1: Find principal (positive) roots EXAMPLE #2: Find n th roots of n th powers (Objective #3) EXAMPLE #3: Figure #2: 7.1 Radical
More informationVol. 5, No. 6 June 2014 ISSN Journal of Emerging Trends in Computing and Information Sciences CIS Journal. All rights reserved.
Optimal Synthesis of Finite State Machines with Universal Gates using Evolutionary Algorithm 1 Noor Ullah, 2 Khawaja M.Yahya, 3 Irfan Ahmed 1, 2, 3 Department of Electrical Engineering University of Engineering
More informationSome algorithmic and combinatorial problems on permutation classes
Some algorithmic and combinatorial problems on permutation classes The point of view of decomposition trees PhD Defense, 2009 December the 4th Outline 1 Objects studied : Permutations, Patterns and Classes
More informationIntroduction to Fractions
Introduction to Fractions A fraction is a quantity defined by a numerator and a denominator. For example, in the fraction ½, the numerator is 1 and the denominator is 2. The denominator designates how
More informationEnumeration of Two Particular Sets of Minimal Permutations
3 47 6 3 Journal of Integer Sequences, Vol. 8 (05), Article 5.0. Enumeration of Two Particular Sets of Minimal Permutations Stefano Bilotta, Elisabetta Grazzini, and Elisa Pergola Dipartimento di Matematica
More informationCSE 573 Problem Set 1. Answers on 10/17/08
CSE 573 Problem Set. Answers on 0/7/08 Please work on this problem set individually. (Subsequent problem sets may allow group discussion. If any problem doesn t contain enough information for you to answer
More informationArtificial Intelligence. 4. Game Playing. Prof. Bojana Dalbelo Bašić Assoc. Prof. Jan Šnajder
Artificial Intelligence 4. Game Playing Prof. Bojana Dalbelo Bašić Assoc. Prof. Jan Šnajder University of Zagreb Faculty of Electrical Engineering and Computing Academic Year 2017/2018 Creative Commons
More informationUMBC CMSC 671 Midterm Exam 22 October 2012
Your name: 1 2 3 4 5 6 7 8 total 20 40 35 40 30 10 15 10 200 UMBC CMSC 671 Midterm Exam 22 October 2012 Write all of your answers on this exam, which is closed book and consists of six problems, summing
More informationLecture Notes on Game Theory (QTM)
Theory of games: Introduction and basic terminology, pure strategy games (including identification of saddle point and value of the game), Principle of dominance, mixed strategy games (only arithmetic
More informationHow (Information Theoretically) Optimal Are Distributed Decisions?
How (Information Theoretically) Optimal Are Distributed Decisions? Vaneet Aggarwal Department of Electrical Engineering, Princeton University, Princeton, NJ 08544. vaggarwa@princeton.edu Salman Avestimehr
More informationGenerating indecomposable permutations
Discrete Mathematics 306 (2006) 508 518 www.elsevier.com/locate/disc Generating indecomposable permutations Andrew King Department of Computer Science, McGill University, Montreal, Que., Canada Received
More informationChapter 7. Intro to Counting
Chapter 7. Intro to Counting 7.7 Counting by complement 7.8 Permutations with repetitions 7.9 Counting multisets 7.10 Assignment problems: Balls in bins 7.11 Inclusion-exclusion principle 7.12 Counting
More informationApplication of Fourier Transform in Signal Processing
1 Application of Fourier Transform in Signal Processing Lina Sun,Derong You,Daoyun Qi Information Engineering College, Yantai University of Technology, Shandong, China Abstract: Fourier transform is a
More informationEMVA1288 compliant Interpolation Algorithm
Company: BASLER AG Germany Contact: Mrs. Eva Tischendorf E-mail: eva.tischendorf@baslerweb.com EMVA1288 compliant Interpolation Algorithm Author: Jörg Kunze Description of the innovation: Basler invented
More informationA Student Scheduling System for Federal Law Enforcement Training Centers (FLETC)
A Student Scheduling System for Federal Law Enforcement Training Centers (FLETC) Frederik Fiand FrederikFiand@googlemail.com Diploma Thesis at the Institute for Mathematical Optimization, TU Braunschweig
More informationLecture 9: Spread Spectrum Modulation Techniques
Lecture 9: Spread Spectrum Modulation Techniques Spread spectrum (SS) modulation techniques employ a transmission bandwidth which is several orders of magnitude greater than the minimum required bandwidth
More informationContinuous time and Discrete time Signals and Systems
Continuous time and Discrete time Signals and Systems 1. Systems in Engineering A system is usually understood to be an engineering device in the field, and a mathematical representation of this system
More informationAlgorithms and Data Structures: Network Flows. 24th & 28th Oct, 2014
Algorithms and Data Structures: Network Flows 24th & 28th Oct, 2014 ADS: lects & 11 slide 1 24th & 28th Oct, 2014 Definition 1 A flow network consists of A directed graph G = (V, E). Flow Networks A capacity
More informationBasic electronics Prof. T.S. Natarajan Department of Physics Indian Institute of Technology, Madras Lecture- 17. Frequency Analysis
Basic electronics Prof. T.S. Natarajan Department of Physics Indian Institute of Technology, Madras Lecture- 17 Frequency Analysis Hello everybody! In our series of lectures on basic electronics learning
More informationDETERMINATION OF JOINT DIAGRAMS FOR A FOUNDATION BOLTED JOINT WITH THE BOLT ANCHORED IN A POLYMER PLASTIC
COMMITTEE OF MECHANICAL ENGINEERING PAS POZNAN DIVISION Vol. 32 no. 3 Archives of Mechanical Technology and Automation 2012 PAWE GRUDZI SKI DETERMINATION OF JOINT DIAGRAMS FOR A FOUNDATION BOLTED JOINT
More informationPearson Edexcel GCE Decision Mathematics D2. Advanced/Advanced Subsidiary
Pearson Edexcel GCE Decision Mathematics D2 Advanced/Advanced Subsidiary Wednesday 29 June 2016 Morning Time: 1 hour 30 minutes Paper Reference 6690/01 You must have: D2 Answer Book Candidates may use
More information9th International DAAAM Baltic Conference "INDUSTRIAL ENGINEERING" April 2014, Tallinn, Estonia
9th International DAAAM Baltic Conference "INDUSTRIAL ENGINEERING" 24-26 April 2014, Tallinn, Estonia DEVELOPMENT OF THE INTELLIGENT FORECASTING MODEL FOR MANUFACTURING COST ESTIMATION IN POLYJET PROCESS
More information