Xinjie Yu

Mitsuo Gen

Evolutionary algorithms are becoming increasingly attractive across various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science and economics. Introduction to Evolutionary Algorithms presents an insightful, comprehensive, and up-to-date treatment of evolutionary algorithms. It covers such hot topics as: • genetic algorithms, • differential evolution, • swarm intelligence, and • artificial immune systems. The reader is introduced to a range of applications, as Introduction to Evolutionary Algorithms demonstrates how to model real world problems, how to encode and decode individuals, and how to design effective search operators according to the chromosome structures with examples of constraint optimization, multiobjective optimization, combinatorial optimization, and supervised/unsupervised learning. This emphasis on practical applications will benefit all students, whether they choose to continue their academic career or to enter a particular industry. Introduction to Evolutionary Algorithms is intended as a textbook or self-study material for both advanced undergraduates and graduate students. Additional features such as recommended further reading and ideas for research projects combine to form an accessible and interesting pedagogical approach to this widely used discipline.

Introduction to Evolutionary Algorithms

Runwei Cheng

Lin Lin

Network models are critical tools in business, management, science and industry. “Network Models and Optimization” presents an insightful, comprehensive, and up-to-date treatment of multiple objective genetic algorithms to network optimization problems in many disciplines, such as engineering, computer science, operations research, transportation, telecommunication, and manufacturing. The book extensively covers algorithms and applications, including shortest path problems, minimum cost flow problems, maximum flow problems, minimum spanning tree problems, traveling salesman and postman problems, location-allocation problems, project scheduling problems, multistage-based scheduling problems, logistics network problems, communication network problem, and network models in assembly line balancing problems, and airline fleet assignment problems. The book can be used both as a student textbook and as a professional reference for practitioners who use network optimization methods to model and solve problems.

Multiobjective Genetic Algorithm Approach

Network Models and Optimization

Kuinam J. Kim

Xiaoxia Huang

Yabe Hiroshi

This volume provides a complete record of presentations made at Industrial Engineering, Management Science and Applications 2015 (ICIMSA 2015), and provides the reader with a snapshot of current knowledge and state-of-the-art results in industrial engineering, management science and applications. The goal of ICIMSA is to provide an excellent international forum for researchers and practitioners from both academia and industry to share cutting-edge developments in the field and to exchange and distribute the latest research and theories from the international community. The conference is held every year, making it an ideal platform for people to share their views and experiences in industrial engineering, management science and applications related fields.

Industrial Engineering, Management Science and Applications 2015

Stefan Nickel

Jiuping Xu

Asaf Hajiyev

This book presents the proceedings of the Tenth International Conference on Management Science and Engineering Management (ICMSEM2016) held from August 30 to September 02, 2016 at Baku, Azerbaijan and organized by the International Society of Management Science and Engineering Management, Sichuan University (Chengdu, China) and Ministry of Education of Azerbaijan. The aim of conference was to foster international research collaborations in management science and engineering management as well as to provide a forum to present current research findings. The presented papers were selected and reviewed by the Program Committee, made up of respected experts in the area of management science and engineering management from around the globe. The contributions focus on identifying management science problems in engineering, innovatively using management theory and methods to solve engineering problems effectively and establishing novel management theories and methods to address new engineering management issues.

Proceedings of the Tenth International Conference on Management Science and Engineering Management

Gürsel A. Süer

The chapters included in this book represent the work from the US, Canada, Japan, China, India, Iran, Netherlands, Turkey, Slovakia, and Portugal. The book attempts to cover the cellular manufacturing area from various angles. In terms of solution techniques, different approaches such as heuristics, mathematical models, networks models, genetic algorithm approaches, artificial neural networks, knowledge-based algorithms, a space search algorithm, simulated annealing, fuzzy concepts, analytic hierarchy processes and simulation are included in the book. As for performance measures, most chapters target a single objective whereas some others cover multiple objectives. In terms of the complexity of the problems, the authors divide them into simpler single phase problems versus more complex problems that require multiple-phase solutions. Most of the chapters discuss deterministic problems. On the other hand, a few of the chapters focus on stochastic cases. There are many new concepts and solution approaches covered in this book. The details of the material coverage is listed in the following paragraphs. The book starts with the evolution of cellular manufacturing. In terms of design-related issues, it covers the application of math modeling for cell formation, family and subfamily formation, production system selection, formation and evaluation of design alternatives, machine layout, dynamic cells, virtual cells, cell formation considering alternative routes, remainder cells, cell formation with product of life cycle considerations, demand-variability based cell formation, layered cellular design, assembly cells and a recent Japanese proposition called SERU cells. All types of cells, namely labor-intensive cells, machine-intensive cells and robotic cells are covered in the book. In terms of operational and control issues, human skills, manpower allocation, cell size determination, dispatching rules, parallel machine scheduling, flowshop scheduling, re-entrant flowshop scheduling, flexible job shop scheduling, assembly line balancing, process planning and scheduling, multiple-resource scheduling, cell loading and cell scheduling, synchronized flow, planning concepts such as period batch control, polka, Kanban, conwip and more are discussed. Cases studies include electromechanical assembly, bicycle manufacturing, igniter assembly system, jewelry manufacturing and semi-conductor industry. We believe that this book will be of value to students, researchers, academicians and practitioners.

Recent Developments, Analysis and Case Studies

Cellular Manufacturing Systems

Syed Ejaz Ahmed

Fang Lee Cooke

This proceedings book is divided in 2 Volumes and 8 Parts. Part I is dedicated to Decision Support System, which is about the information system that supports business or organizational decision-making activities; Part II is on Computing Methodology, which is always used to provide the most effective algorithm for numerical solutions of various modeling problems; Part III presents Information Technology, which is the application of computers to store, study, retrieve, transmit and manipulate data, or information in the context of a business or other enterprise; Part IV is dedicated to Data Analysis, which is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making; Part V presents papers on Operational Management, which is about the plan, organization, implementation and control of the operation process; Part VI is on Project Management, which is about the initiating, planning, executing, controlling, and closing the work of a team to achieve specific goals and meet specific success criteria at the specified time in the field of engineering; Part VII presents Green Supply Chain, which is about the management of the flow of goods and services based on the concept of “low-carbon”; Part VIII is focused on Industry Strategy Management, which refers to the decision-making and management art of an industry or organization in a long-term and long-term development direction, objectives, tasks and policies, as well as resource allocation.

Proceedings of the Twelfth International Conference on Management Science and Engineering Management

A comprehensive guide to a powerful new analytical tool by two of its foremost innovators The past decade has witnessed many exciting advances in the use of genetic algorithms (GAs) to solve optimization problems in everything from product design to scheduling and client/server networking. Aided by GAs, analysts and designers now routinely evolve solutions to complex combinatorial and multiobjective optimization problems with an ease and rapidity unthinkable withconventional methods. Despite the continued growth and refinement of this powerful analytical tool, there continues to be a lack of up-to-date guides to contemporary GA optimization principles and practices. Written by two of the world's leading experts in the field, this book fills that gap in the literature. Taking an intuitive approach, Mitsuo Gen and Runwei Cheng employ numerous illustrations and real-world examples to help readers gain a thorough understanding of basic GA concepts-including encoding, adaptation, and genetic optimizations-and to show how GAs can be used to solve an array of constrained, combinatorial, multiobjective, and fuzzy optimization problems. Focusing on problems commonly encountered in industry-especially in manufacturing-Professors Gen and Cheng provide in-depth coverage of advanced GA techniques for: * Reliability design * Manufacturing cell design * Scheduling * Advanced transportation problems * Network design and routing Genetic Algorithms and Engineering Optimization is an indispensable working resource for industrial engineers and designers, as well as systems analysts, operations researchers, and management scientists working in manufacturing and related industries. It also makes an excellent primary or supplementary text for advanced courses in industrial engineering, management science, operations research, computer science, and artificial intelligence.

Mitsuo Gen

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