Masters' Theses Production Planning and Distribution Planning using Demand based mixed Genetic Algorithm in a Supply Chain
2015.07.29 13:49
| year | 2003 |
|---|---|
| author | Jung Im |
| Keyword | SCM, Production Planning, Distribution Planning, Genetic Algorithm |
| Abstract | Due to the emergence of e-Business and supply chain, manufacturers these days have to make diverse decisions concerning their production activities. Especially, decisions on production and distribution planning need to consider demands, technical requirements and capacity constraints all at the same time using real time information from all the sites in a supply chain. But the production and distribution planning problem is a combined optimization problem where the computing time increases combinatorially in proportion to the complexity of the problem. Hence, development of an algorithm that gives a workable solution in a timely manner is needed. In this study, we propose a rule-based mixed genetic algorithm to solve production and distribution planning problem in a supply chain considering demand characteristics and capacity constraints in each site. The algorithm starts from an initial solution that is generated using the specially transformed demand information. And we add special rules to the genetic algorithm to avoid infeasibility. Finally we propose a modified crossover to get a better solution. Experimental results show that the proposed algorithm generates relatively good performance in almost real time. |
| c | MS |
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