In this paper, we investigate the Single-Source Capacitated Multi-Facility Weber Problem. The aim is to locate several new facilities among existing customers and simultaneously allocate customers to the facilities. A Genetic Algorithm is proposed for solving the problem, in which a local search method is embedded. The proposed Genetic Algorithm is tested on existing data sets to evaluate its robustness over available methods in the literature. Manuscript profile

Here, we will study the Single-Source Capacitated Multi-Facility Weber Problem with Setup Costs (SSCMFWP-SC) to find location of certain numbers of facilities in continuous space so that demands by certain numbers of customers would be satisfied. This would be done in a way that total transportation cost between customers and facilities as well as total setup cost would be minimized. Facilities have limited capacity and each customer has to satisfy all of its demands just from one facility. Setup cost of facilities is variable and dependent on combination of machineries used by each facility. To solve the problem, Two versions of the proposed heuristic method named iterative random search will be presented in which local search method and exact solution method are used. proposed method has been tested on a dataset available in the literature and the obtained solutions compared to the best of them in the literatures. The results show extraordinary performance of recommended methods. Moreover, best available solutions in the literature have been improved and the best obtained solutions can be used as a comparison source in future studies. Manuscript profile