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Book A Composite Heuristic for the Identical Parallel Machine Scheduling Problem with Minimum Makespan Objective

Download or read book A Composite Heuristic for the Identical Parallel Machine Scheduling Problem with Minimum Makespan Objective written by França, P. M and published by Montréal : Centre for Research on Transportation = Centre de recherche sur les transports. This book was released on 1992 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Metaheuristics for Scheduling in Industrial and Manufacturing Applications

Download or read book Metaheuristics for Scheduling in Industrial and Manufacturing Applications written by Fatos Xhafa and published by Springer Science & Business Media. This book was released on 2008-06-21 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the past decades scheduling has been among the most studied op- mization problemsanditisstillanactiveareaofresearch!Schedulingappears in many areas of science, engineering and industry and takes di?erent forms depending on the restrictions and optimization criteria of the operating en- ronments [8]. For instance, in optimization and computer science, scheduling has been de?ned as “the allocation of tasks to resources over time in order to achieve optimality in one or more objective criteria in an e?cient way” and in production as “production schedule, i. e. , the planning of the production or the sequence of operations according to which jobs pass through machines and is optimal with respect to certain optimization criteria. ” Although there is a standardized form of stating any scheduling problem, namely “e?cient allocation ofn jobs onm machines –which can process no more than one activity at a time– with the objective to optimize some - jective function of the job completion times”, scheduling is in fact a family of problems. Indeed, several parameters intervene in the problem de?nition: (a) job characteristics (preemptive or not, precedence constraints, release dates, etc. ); (b) resource environment (single vs. parallel machines, un- lated machines, identical or uniform machines, etc. ); (c) optimization criteria (minimize total tardiness, the number of late jobs, makespan, ?owtime, etc. ; maximize resource utilization, etc. ); and, (d) scheduling environment (static vs. dynamic,intheformerthenumberofjobstobeconsideredandtheirready times are available while in the later the number of jobs and their charact- istics change over time).

Book Experimental and Efficient Algorithms

Download or read book Experimental and Efficient Algorithms written by Celso C. Ribeiro and published by Springer. This book was released on 2004-04-20 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Workshop on Experimental and Efficient Algorithms, WEA 2004, held in Angra dos Reis, Brazil in May 2004. The 40 revised full papers presented together with abstracts of two invited talks were carefully reviewed and selected from numerous submissions. The book is devoted to the areas of design, analysis, and experimental evaluation of algorithms. Among the topics covered are scheduling, heuristics, combinatorial optimization, evolutionary optimization, graph computations, labeling, robot navigation, shortest path algorithms, flow problems, searching, randomization and derandomization, string matching, graph coloring, networking, error detecting codes, timetabling, sorting, energy minimization, etc.

Book Identical Parallel Machine Scheduling Problems

Download or read book Identical Parallel Machine Scheduling Problems written by Alexander Lawrinenko and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The work is about fundamental parallel machine scheduling problems which occur in manufacturing systems where a set of jobs with individual processing times has to be assigned to a set of machines with respect to several workload objective functions like makespan minimization, machine covering or workload balancing. In the first chapter of the work an up-to-date survey on the most relevant literature for these problems is given, since the last review dealing with these problems has been published almost 20 years ago. We also give an insight into the relevant literature contributed by the Artificial Intelligence community, where the problem is known as number partitioning. The core of the work is a universally valid characterization of optimal makespan and machine-covering solutions where schedules are evaluated independently from the processing times of the jobs. Based on these novel structural insights we derive several strong dominance criteria. Implemented in a branch-and-bound algorithm these criteria have proved to be effective in limiting the solution space, particularly in the case of small ratios of the number of jobs to the number of machines. Further, we provide a counter-example to a central result by Ho et al. (2009) who proved that a schedule which minimizes the normalized sum of squared workload deviations is necessarily a makespan-optimal one. We explain why their proof is incorrect and present computational results revealing the difference between workload balancing and makespan minimization. The last chapter of the work is about the minimum cardinality bin covering problem which is a dual problem of machine-covering with respect to bounding techniques. We discuss reduction criteria, derive several lower bound arguments and propose construction heuristics as well as a subset sum-based improvement algorithm. Moreover, we present a tailored branch-and-bound method which is able to solve instances with up to 20 bins.

Book Local Search in Combinatorial Optimization

Download or read book Local Search in Combinatorial Optimization written by Emile Aarts and published by Princeton University Press. This book was released on 2018-06-05 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past three decades, local search has grown from a simple heuristic idea into a mature field of research in combinatorial optimization that is attracting ever-increasing attention. Local search is still the method of choice for NP-hard problems as it provides a robust approach for obtaining high-quality solutions to problems of a realistic size in reasonable time. Local Search in Combinatorial Optimization covers local search and its variants from both a theoretical and practical point of view, each topic discussed by a leading authority. This book is an important reference and invaluable source of inspiration for students and researchers in discrete mathematics, computer science, operations research, industrial engineering, and management science. In addition to the editors, the contributors are Mihalis Yannakakis, Craig A. Tovey, Jan H. M. Korst, Peter J. M. van Laarhoven, Alain Hertz, Eric Taillard, Dominique de Werra, Heinz Mühlenbein, Carsten Peterson, Bo Söderberg, David S. Johnson, Lyle A. McGeoch, Michel Gendreau, Gilbert Laporte, Jean-Yves Potvin, Gerard A. P. Kindervater, Martin W. P. Savelsbergh, Edward J. Anderson, Celia A. Glass, Chris N. Potts, C. L. Liu, Peichen Pan, Iiro Honkala, and Patric R. J. Östergård.

Book Optimization in Artificial Intelligence and Data Sciences

Download or read book Optimization in Artificial Intelligence and Data Sciences written by Lavinia Amorosi and published by Springer Nature. This book was released on 2022-05-20 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is addressed to researchers in operations research, data science and artificial intelligence. It collects selected contributions from the first hybrid “Optimization and Decision Science - ODS2021” international conference on the theme Optimization and Artificial Intelligence and Data Sciences, which was held in Rome 14-17 September 2021 and organized by AIRO, the Italian Operations Research Society and the Department of Statistical Sciences of Sapienza University of Rome. The book offers new and original contributions on different methodological optimization topics, from Support Vector Machines to Game Theory Network Models, from Mathematical Programming to Heuristic Algorithms, and Optimization Methods for a number of emerging problems from Truck and Drone delivery to Risk Assessment, from Power Networks Design to Portfolio Optimization. The articles in the book can give a significant edge to the general themes of sustainability and pollution reduction, distributive logistics, healthcare management in pandemic scenarios and clinical trials, distributed computing, scheduling, and many others. For these reasons, the book is aimed not only at researchers in the Operations Research community but also for practitioners facing decision-making problems in these areas and to students and researchers from other disciplines, including Artificial Intelligence, Computer Sciences, Finance, Mathematics, and Engineering.

Book Intelligent Systems and Applications

Download or read book Intelligent Systems and Applications written by Kohei Arai and published by Springer Nature. This book was released on 2020-08-06 with total page 773 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book Intelligent Systems and Applications - Proceedings of the 2020 Intelligent Systems Conference is a remarkable collection of chapters covering a wider range of topics in areas of intelligent systems and artificial intelligence and their applications to the real world. The Conference attracted a total of 545 submissions from many academic pioneering researchers, scientists, industrial engineers, students from all around the world. These submissions underwent a double-blind peer review process. Of those 545 submissions, 177 submissions have been selected to be included in these proceedings. As intelligent systems continue to replace and sometimes outperform human intelligence in decision-making processes, they have enabled a larger number of problems to be tackled more effectively.This branching out of computational intelligence in several directions and use of intelligent systems in everyday applications have created the need for such an international conference which serves as a venue to report on up-to-the-minute innovations and developments. This book collects both theory and application based chapters on all aspects of artificial intelligence, from classical to intelligent scope. We hope that readers find the volume interesting and valuable; it provides the state of the art intelligent methods and techniques for solving real world problems along with a vision of the future research.

Book Experimental and Efficient Algorithms

Download or read book Experimental and Efficient Algorithms written by and published by . This book was released on 2004 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Model and Algorithms for Scheduling Uniform Parallel Machines

Download or read book Model and Algorithms for Scheduling Uniform Parallel Machines written by P Senthilkumar and published by Independently Published. This book was released on 2024-01-18 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Production scheduling helps businesses become more productive and efficiently satisfy consumer needs. Because it falls within the combinatorial category, scheduling work on uniform parallel computers to minimize the makespan measure is a difficult problem under single machine scheduling. The goal of this essay is to show how to design an effective algorithm for this particular situation. The introduction chapter of this text covers single machine scheduling with a single machine, single machine scheduling with parallel machines, and research gap of unform parallel machine scheduling. The goals of the challenge, the assumptions behind the scheduling of uniform parallel machines, and the plan for developing the algorithms are all presented in Chapter 2, which describes the problem. A model and an example of the model utilizing a small size problem are provided in Chapter 3 on the mathematical model for uniform parallel machines scheduling to minimize makespan. The simulated annealing algorithm to minimize makespan in the single machine scheduling problem with uniform parallel machines is presented in Chapter 4. It includes an overview of the algorithm, its skeleton, three newly developed simulated annealing algorithms, and a comparison of them to determine which is the best. The development of a GA-based strategy to reduce the uniform parallel machine scheduling makespan is presented in Chapter 5. This covers the basic structure of the genetic algorithm, factors that impact the GA algorithm, techniques for assigning tasks to machines, and crossover strategies. Additionally, it entails the creation of four GA-based heuristics to reduce makespan and a comparison of them to determine which GA-based heuristic is optimum for scheduling jobs on uniform parallel computers. In order to determine which is optimal, the best GA-based heuristic and the best simulated annealing technique are compared in Chapter 6 to minimize the makespan of scheduling jobs on uniform parallel computers. Appendix 1 for replication 1 and Appendix 2 for replication 2 contain the data needed to test the heuristics in Chapter 4, Chater 5, and Chapter 6. The author expresses gratitude to all of his university colleagues and academicians for their support in releasing this work. The writing style of this text is simple to read. P. Senthilkumar, B.E., M.E., Ph.D

Book Handbook of combinatorial optimization

Download or read book Handbook of combinatorial optimization written by Dingzhu Du and published by Springer Science & Business Media. This book was released on 1998-12-15 with total page 880 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combinatorial (or discrete) optimization is one of the most active fields in the interface of operations research, computer science, and applied math ematics. Combinatorial optimization problems arise in various applications, including communications network design, VLSI design, machine vision, air line crew scheduling, corporate planning, computer-aided design and man ufacturing, database query design, cellular telephone frequency assignment, constraint directed reasoning, and computational biology. Furthermore, combinatorial optimization problems occur in many diverse areas such as linear and integer programming, graph theory, artificial intelligence, and number theory. All these problems, when formulated mathematically as the minimization or maximization of a certain function defined on some domain, have a commonality of discreteness. Historically, combinatorial optimization starts with linear programming. Linear programming has an entire range of important applications including production planning and distribution, personnel assignment, finance, alloca tion of economic resources, circuit simulation, and control systems. Leonid Kantorovich and Tjalling Koopmans received the Nobel Prize (1975) for their work on the optimal allocation of resources. Two important discover ies, the ellipsoid method (1979) and interior point approaches (1984) both provide polynomial time algorithms for linear programming. These algo rithms have had a profound effect in combinatorial optimization. Many polynomial-time solvable combinatorial optimization problems are special cases of linear programming (e.g. matching and maximum flow). In addi tion, linear programming relaxations are often the basis for many approxi mation algorithms for solving NP-hard problems (e.g. dual heuristics)."

Book Development and Evaluation of Setup Strategies in Printed Circuit Board Assembly

Download or read book Development and Evaluation of Setup Strategies in Printed Circuit Board Assembly written by Ihsan Onur Yilmaz and published by Springer Science & Business Media. This book was released on 2008-09-27 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ihsan Onur Yilmaz develops a novel group setup strategy which integrates multiple problems of the PCB assembly, especially in a medium-variety production environment.

Book Meta RaPS for a Bi objective Unrelated Parallel Machine Scheduling Problem

Download or read book Meta RaPS for a Bi objective Unrelated Parallel Machine Scheduling Problem written by Nixon Dcoutho and published by . This book was released on 2015 with total page 73 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis discusses the capability and effectiveness of a meta-heuristic for Randomized Priority Search to solve multi-objective problems. The multi-objective problem of unrelated parallel machine scheduling is considered in the thesis. The two objectives to minimize are total weighted tardiness and total weighted completion time. Two approaches are suggested to solve the problem. The first approach uses an existing construction rule in the literature named Apparent Tardiness Cost-bi heuristic, which is used as the basis for the meta-heuristic construction phase in Meta-RaPS to generate non-dominated solutions. The computational results obtained are promising when results of the meta-heuristic approach proposed are compared with those of the original construction rule. In the second approach, memory mechanism is incorporated in the construction phase of Meta-RaPS to solve the problem. The computational results obtained show that Meta-RaPS performs better with memory. This thesis illustrates that the meta-heuristic approach proposed is effective and flexible enough to generate Pareto frontiers in order to solve multi-objective scheduling problems.

Book Heuristics for Parallel Machine Scheduling with Delivery Times

Download or read book Heuristics for Parallel Machine Scheduling with Delivery Times written by Gerhard J. Woeginger and published by . This book was released on 1991 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "A parallel machine scheduling problem is considered in which each job has a processing time and a delivery time. The objective is to find a schedule which minimizes the time by which all jobs are delivered. For the single machine this problem is easily solved in polynomial time, for m [> or =] machines it becomes NP-hard. Several heuristics using list scheduling as a subroutine are proposed and analysed. The best one of our heuristics has a worst-case performance guarantee of 2 - 2 / (m + 1). For the on-line case we give a heuristic with the (best possible) worst-case performance of two."