A new GA based solution for capacitated multi source Weber problem

The main purpose of any facility location is to select the optimal places that satisfy project's goals. In location problems, the object is usually to optimize a function objective function that defines the problem conditions and efficient decision parameters. Numerous methods are proposed to challenge the location facility issues. In this paper, we consider a class of location/allocation problem that can assume more realistic conditions in real-life applications. This problem is an extension to the well-known capacitated multi source Weber problem. A new method that uses two genetic algorithms is used to solve the problem efficiently. The first, External GA, solves the location problem while the second, Internal GA, solves the allocation problem. A case study was designed to assess the feasibility of the proposed solution. The results indicate that the new approach is optimal, efficient and successful.