GA applications to physical distribution scheduling problem

A physical distribution system has a number of optimization problems. Most of them belong to a combinatorial problem, to which conventional mathematical programming methods may hardly be applied. This paper reports on some applications of the genetic algorithm (GA) to the physical distribution scheduling problems, which are arising at the real physical distribution centers. The developed GA schedulers took the place of conventional schedulers, which were coded by rule-based technologies. Advantages to introduce the GA scheduler into the physical distribution systems are as follows; (1) the GA becomes a general problem solver engine. Once we develop this engine, we only have to develop interfaces for the applications. (2) Fitness functions necessary for the GA force the physical distribution schedule to have an approximate estimation. This is not taken into consideration when the rule-based scheduler is used. Two applications of the discussed schedulers were implemented with the real distribution centers and they brought much management efficiency