| Description |
1 online resource (xvii, 341 pages) : illustrations |
| Bibliography |
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, João P.S. Catalão. |
| 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 |
| Subject |
Scheduling -- Mathematical models.
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Evolutionary computation.
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Mathematical optimization.
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Swarm intelligence.
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Emploi du temps -- Modèles mathématiques. |
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Réseaux neuronaux à structure évolutive. |
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Optimisation mathématique. |
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Evolutionary computation |
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Mathematical optimization |
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Scheduling -- Mathematical models |
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Swarm intelligence |
| Added Author |
Gandomi, Amir Hossein, editor.
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Emrouznejad, Ali, editor.
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Jamshidi, Mohammad, editor.
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Deb, Kalyanmoy, editor.
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Rahimi, Iman, editor.
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| Other Form: |
Print version: Evolutionary computation in scheduling. Hoboken, NJ : Wiley, 2020 9781119573845 (DLC) 2019056751 |
| ISBN |
9781119573876 (electronic publication) |
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1119573874 (electronic publication) |
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9781119573869 (adobe electronic book) |
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1119573866 (adobe electronic book) |
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9781119574293 (electronic bk.) |
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1119574293 (electronic bk.) |
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(hardcover) |
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(hardcover) |
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