Iterative random search heuristic for the Single-Source Capacitated Multi-Facility Weber Problem with Setup Costs
محورهای موضوعی : Meta-heurestics
1 - Faculty of Industrial Engineering, Urmia University of Technology, Urmia, Iran
کلید واژه: Location-allocation, heuristic algorithm, Weber problem, Setup cost, Random search,
چکیده مقاله :
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.
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.
