The Genetic Algorithms for Dynamic Order Volume with Randomly and Inconsecutively Demands
The problems of inventory management demand which has random variation of products as well as demand in each interval which have many opportunities in discrete value are the problems that quite difficult to find quantity order as demand have many alternatives. If we did not receive products immediately after being ordered, we had to plan the long-term condition for a while on order to get a suitable option. The solutions for this problem have many ways, this report will thus present two solutions. They are 1) Stochastic Integer Linear Programming (SILP) and 2) Genetic Algorithm (GA) by defining the stable products prices that do not vary by the time before testing with 24 model problems. As a consequence, both solutions provided the right answer for random demand dynamic ordering problem. However, the time to find the answers are of difference. SILP can provide more accurate answer compared with GA, but SILP is proper for small problems which less than 6 periods and GA proper for big problems which has complexity of less than 11 periods.
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