Multiobjective Scheduling By Genetic Algorithms
About The This book is therefore intended for students of industrial engineering, operations research, operations management and computer science, as well as practitioners.. Also it accents the value of hybridizing Gas with both solution-generating and solution-improvement methods
Multiobjective Scheduling by Genetic Algorithms describes methods for developing multiobjective solutions to common production scheduling equations modeling in the literature as flowshops, job shops and open shops. This text shows how methods such as Elitist Nondominated Sorting Genetic Algorithm (ENGA) can find a bevy of Pareto optimal solutions for them. The methodology is metaheuristic, one inspired by how nature has evolved a multitude of coexisting species of living beings on earth. It envisions fundamental research into such methods, greatly strengthening the growing reach of metaheuristic methods. It may also assist in the development of efficient shop management software tools for schedulers and production planners who face multiple planning and operating objectives as a matter of course. Also it accents the value of hybridizing Gas with both solution-generating and solution-improvement methods. Multiobjective flowshops, job shops and open shops are each highly relevant models in manufacturing, classroom scheduling or automotive assembly, yet for want of sound methods they have remained almost untouched to date. This book is therefore intended for students of industrial engineering, operations research, operations management and computer science, as well as practitioners.
Books > Business and Management
Multiobjective Scheduling By Genetic Algorithms
Books > Business and Management
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