Using NSGA-II to solve multi-objective competitive location problem with cooperative coverage for distance-based attractiveness

Abstract

Multi-objective competitive location problem with cooperative coverage for distance-based attractiveness is introduced in this paper. The potential facilities compete to be selected to serve all demand points which are determined by maximizing total collective attractiveness of all demand points from assigned facilities and minimizing the fixed and distance costs between all demand points and selected facilities. Facility attractiveness is represented as a coverage of the facility with full, partial and none coverage corresponding to maximum full and partial coverage radii. Cooperative coverage, which the demand point is covered by at least one facility, is also considered. The problem is formulated as a multi-objective optimization model and solution procedure based on elitist non-dominated sorting genetic algorithms (NSGA-II) is developed. Experimental example demonstrates the best non-dominated solution sets obtained by developed solution procedure. Contributions of this paper include introducing competitive location problem with facility attractiveness as a distance-based coverage of the facility, re-categorizing facility coverage classification and developing solution procedure base upon NSGA-II.

A Hybrid Approach of VIKOR and Bi-Objective Decision Model for Emergency Shelter Location–Allocation to Respond to Earthquakes

“…The collective coverage model can be used to study the problem of emergency shelter location. One of the key assumptions of the collective coverage model is that if the distance between the demand point and the facility is not greater than r, the demand point is assumed to be completely covered, otherwise, the demand point is not covered [11]. However, in non-routine projects, it is difficult to accurately predict the integrity of the shelter and whether the victims are willing to go to the recommended shelter.…”