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Multiobjective Resource Allocation Problems By Multistage Hybrid Genetic Algorithm
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Multiobjective Resource Allocation Problems By Multistage Hybrid Genetic Algorithm
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Multiobjective Resource Allocation Problems By Multistage Hybrid Genetic Algorithm Multiobjective Resource Management Problems (m-RMP) involves deciding how to divide a resource of limited availability among multiple demands in a way that optimizes current objectives. RMP is widely used to plan the optimal allocating or management resources process among various projects or business units for the maximum product and the minimum cost. “Resources” might be manpower, assets, raw materials, capital or anything else in limited supply. The solution method of RMP, however, has its own problems; this book identifies four of them along with the proposed methods to solve them. Mathematical models combined with effective multistage Genetic Algorithm (GA) approach help to develop a method for handling the m-RMP. The proposed approach not only can solve relatively large size problems but also has better performance than the conventional GA. And the proposed method provides more flexibility to m-RMP model which is the key to survive under severely competitive environment. We also believe that the proposed method can be adapted to other production-distribution planning and all m-RAP models. In this book, four problems with m-RMP models will be clearly outlined and a multistage hybridized GA method for finding the best solution is then implemented. Comparison results with the conventional GA methods are also presented. This book also mentions several useful combinatorial optimization models in process system and proposed effective solution methods by using multistage GA. Note¡GPart of this book, once published in international journals SCI (Science Direct) inside, be accepted have five articles.
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