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Title Evolutionary computation in scheduling / edited by Amir H. Gandomi, Ali Emrouznejad, Mo M. Jamshidi, Kalyanmoy Deb, Iman Rahimi.
Imprint Hoboken, NJ : John Wiley & Sons, Inc., 2020.

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Subject Scheduling -- Mathematical models.
Evolutionary computation.
Mathematical optimization.
Swarm intelligence.
Alt Name Gandomi, Amir Hossein,
Emrouznejad, Ali,
Jamshidi, Mohammad,
Deb, Kalyanmoy,
Rahimi, Iman,
Description 1 online resource (xvii, 341 pages) : illustrations
Bibliography Note Includes bibliographical references and index.
Contents Evolutionary computation in scheduling : a scientometric analysis / Amir H. Gandomi, Ali Emrouznejad, Iman Rahimi -- Role and impacts of ant colony optimization in job shop scheduling problems : a detail analysis / P. Deepalakshmi, K. Shankar -- Advanced ant colony optimization in healthcare scheduling / Reza Behmanesh, Iman Rahimi, Mostafa Zandieh, Amir H. Gandomi -- Task scheduling in heterogeneous computing systems using swarm intelligence / S Sarathambekai, K Umamaheswari -- Computationally efficient scheduling schemes for multiple antenna systems using evolutionary algorithm and swarm optimization / Prabina Pattanayak, Preetam Kumar -- An efficient modified red deer algorithm to solve a truck scheduling problem considering time windows and deadline for trucks' departure / Amir Mohammad Fathollahi-Fard, Abbas Ahmadi, Mohsen S. Sajadieh -- Application of sub-population scheduling algorithm in multi-population evolutionary dynamic optimization / Javidan Kazemi Kordestani, Mohammad Reza Meybodi -- Task scheduling in cloud environments : a survey on population-based evolutionary algorithms / Fahimeh Ramezani, Mohsen Naderpour, Javid Taheri, Jack Romanous, Albert Y. Zomaya -- Scheduling of robotic disassembly in remanufacturing using bees algorithm / Jiayi Liu, Wenjun Xu, Zude Zhou, Duc Truong Pham -- A modified fireworks algorithm to solve the heat and power generation scheduling problem in power system studies / Mohammad Sadegh Javadi, Ali Esmaeel Nezhad, Seyed-Ehsan Razavi, Abdollah Ahmadi, Joao P.S. Catalao.
Summary "This book provides insight into the use of evolutionary computations in real-world applications. This edited book allows the reader to analyze the point of view of each contributor regarding how to choose a specific evolutionary computation and how to validate the results using metrics and statistics. The spectrum of real-world optimization problems dealt with in this book includes, among others, application of EC in industry and service organizations such as healthcare scheduling, aircraft industry, school timetabling, manufacturing systems, and transportation scheduling in the supply chain. Throughout the book, the reader will find not only problems with different degrees of complexity, but also with different practical requirements, user constraints, and a variety of MOEC solution approaches. This book is ideal for engineers in industries, research scholars, advanced undergraduates and graduate students, and faculty teaching and conducting research in Operations Research and Industrial Engineering"-- Provided by publisher
Note Online resource; title from digital title page (viewed on May 14, 2020).
ISBN 9781119573876 (electronic publication)
1119573874 (electronic publication)
9781119573869 (adobe electronic book)
1119573866 (adobe electronic book)
9781119574293 (electronic bk.)
1119574293 (electronic bk.)
9781119573845 (hardcover)
111957384X (hardcover)
OCLC # 1150975805
Additional Format Print version: Evolutionary computation in scheduling. Hoboken, NJ : Wiley, 2020 9781119573845 (DLC) 2019056751

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