| Summary: | To be successful in today’s active business competition, enterprises need to design and build effective flexible logistics networks. Since the flexible multistage logistic network (fMLN) problem is NP-hard, many researchers have attempted to use Meta-heuristics methods such as Genetic Algorithms (GAs) to solve the problem. Previous research works using GA for fMLN only considered the problem as a single source, at least in the last network layer between retailer and customer. In real world, however, the problem is one of multi-source logistics network. In this research, the genetic algorithms with penalty method, called P-GA, is used to solve the multi source single product fMLN problem. It is shown however that the P-GA requires unreasonable elapsed time to obtain an acceptable solution. To speed up the algorithm, the research proceeds with the developments of heuristics rules for initialization, crossover and mutation within P-GA and named as HR-GA. This research shows the proposed HR-GA has substantially reduced the elapsed time to obtain better acceptable solution.
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