Hybrid heuristic for dynamic location-allocation on micro-credit territory design

the location and type of the territory centers from potential branches and allocation of the customer base to these territory centers with respect to particular planning criteria. We utilize the twophase location-allocation optimization approach that was proposed in [1] in order to construct a multi-criteria territory design for a single MF؛. This model considers both the mean and variance of a planning criterion. In order to solve the resulting large scale mixed integer program, we utilize a number of heuristics within a branch and bound framework. This manuscript focuses on the comprehensive statistical analysis that provides insights about the interplay of the heuristics. We discuss the effect of the proposed heuristics on the solution quality and computational time in order to provide insights about their use in the solution of mixed integer programs with large scale instances. Abstract. Th؛s paper presents a two phase mixed integer program for the commercial territory design problem of a micro financing institution. After the locations of the territory centers are determined, the customer allocation is done with respect to such planning criteria as total workload, amount of loans, and profit allocation. ؛n order to solve this model for large instances, we propose a hybrid heuristic that includes fixing variables, perturbation analysis, and dynamic relocation of territory centers. We pe^orm a comprehensive statistical analysis that provides novel insights about the interplay of the heuristics in a large scale mixed integer program. The efficiency of the hybrid heuristic is tested and its effectiveness to find near optimal solutions with a reasonably small computational effort is discussed.