Multiple Warehouses Scheduling Using Steady State Genetic Algorithms
Warehouses scheduling is the problem of sequencing requests of products to fulfill several customers' orders so as to minimize the average time and shipping costs. In this paper, a solution to the problem of multiple warehouses scheduling using the steady state genetic algorithm is presented. A mathematical model that organizes the relationships between customers and warehouses is also presented in this paper. Two scenarios of storage capacities (constants and varying capacities) and two strategies of search points (ideal point and random points) are compared. An analysis of the results indicates that multiple warehouses scheduling using the GENITOR approach with different warehouses capacities have better outcome than the usage of the traditional genetic algorithms).
multiple warehouse scheduling genitor ideal point search strategy random point search strategy