Evolutionary computation in scheduling / edited by Amir H. Gandomi, Ali Emrouznejad, Mo M. Jamshidi, Kalyanmoy Deb, Iman Rahimi.
Contributor(s): Gandomi, Amir Hossein [editor.] | Emrouznejad, Ali [editor.] | Jamshidi, Mohammad [editor.] | Deb, Kalyanmoy [editor.] | Rahimi, Iman [editor.]
Language: English Publisher: Hoboken, New Jersey : John Wiley & Sons, 2020Description: 1 online resource (xvii, 368 pages)Content type: text Media type: computer Carrier type: online resourceISBN: 9781119573876; 9781119573869; 9781119574293Subject(s): Scheduling -- Mathematical models | Evolutionary computation | Mathematical optimization | Swarm intelligenceGenre/Form: Electronic booksAdditional physical formats: Print version:: Evolutionary computation in schedulingDDC classification: 658.5/3 LOC classification: HD69.T54Online resources: Full text available at Wiley Online Library Click here to viewItem type | Current location | Home library | Call number | Status | Date due | Barcode | Item holds |
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COLLEGE LIBRARY | COLLEGE LIBRARY LIC Gateway | 658.53 Ev648 2020 (Browse shelf) | Available | CL-51219 |
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658.5 Sch761 2007 Operations management : contemporary concepts and cases / | 658.5 St48 1999 Production/operations management / | 658.514 Disrupting Finance : FinTech and Strategy in the 21st Century / | 658.53 Ev648 2020 Evolutionary computation in scheduling / | 658.5620218 Sa716 2019 The road to quality control : the industrial application of statistical quality control / | 658.57 G375 2018 Innovation, research and development management / | 658.575 F6461 2019 Managing technology and product development programmes : a framework for success / |
Includes bibliographical references and index.
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.
"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.
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