| 書目名稱 | Multiobjective Scheduling by Genetic Algorithms | | 編輯 | Tapan P. Bagchi | | 視頻video | http://file.papertrans.cn/641/640844/640844.mp4 | | 圖書封面 |  | | 描述 | .Multiobjective Scheduling by Genetic Algorithms. describesmethods for developing multiobjective solutions to common productionscheduling equations modeling in the literature as flowshops, jobshops and open shops. The methodology is metaheuristic, one inspiredby how nature has evolved a multitude of coexisting species of livingbeings on earth. .Multiobjective flowshops, job shops and open shops are each highlyrelevant models in manufacturing, classroom scheduling or automotiveassembly, yet for want of sound methods they have remained almostuntouched to date. This text shows how methods such as .Elitist..Nondominated Sorting Genetic Algorithm. (ENGA) can find a bevy ofPareto optimal solutions for them. Also it accents the value ofhybridizing Gas with both solution-generating and solution-improvementmethods. It envisions fundamental research into such methods, greatlystrengthening the growing reach of metaheuristic methods. .This book is therefore intended for students of industrialengineering, operations research, operations management and computerscience, as well as practitioners. It may also assist in thedevelopment of efficient shop management software tools for schedulersand pro | | 出版日期 | Book 1999 | | 關(guān)鍵詞 | Manufacturing; algorithms; genetic algorithms; modeling; operations research; optimization; production; sch | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4615-5237-6 | | isbn_softcover | 978-1-4613-7387-2 | | isbn_ebook | 978-1-4615-5237-6 | | copyright | Springer Science+Business Media New York 1999 |
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