LEADER 03889nam 2200445 450 001 9910830011903321 005 20200804100614.0 010 $a1-119-57386-6 010 $a1-119-57387-4 010 $a1-119-57429-3 035 $a(CKB)4100000010870964 035 $a(MiAaPQ)EBC6173671 035 $a(CaSebORM)9781119573845 035 $a(EXLCZ)994100000010870964 100 $a20200804d2020 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aEvolutionary computation in scheduling /$fedited by Amir H. Gandomi [and four others] 210 1$aHoboken, NJ :$cJohn Wiley & Sons, Inc.,$d[2020] 210 4$dİ2020 215 $a1 online resource (408 pages) 311 $a1-119-57384-X 327 $aEvolutionary 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, Joa?o P.S. Catala?o. 330 $a"This book provides insight into the use of evolutionary computations in real-world applications. This edited book allows the reader to analyze the point of view of each contributor regarding how to choose a specific evolutionary computation and how to validate the results using metrics and statistics. The spectrum of real-world optimization problems dealt with in this book includes, among others, application of EC in industry and service organizations such as healthcare scheduling, aircraft industry, school timetabling, manufacturing systems, and transportation scheduling in the supply chain. Throughout the book, the reader will find not only problems with different degrees of complexity, but also with different practical requirements, user constraints, and a variety of MOEC solution approaches. This book is ideal for engineers in industries, research scholars, advanced undergraduates and graduate students, and faculty teaching and conducting research in Operations Research and Industrial Engineering"--$cProvided by publisher. 606 $aMathematical optimization$xComputer programs 606 $aScheduling$xMathematical models 615 0$aMathematical optimization$xComputer programs. 615 0$aScheduling$xMathematical models. 676 $a519.3 702 $aGandomi$b Amir H. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830011903321 996 $aEvolutionary computation in scheduling$94040235 997 $aUNINA