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Integration of geographical information systems, meta-heuristics and optimization models for the employee transportation problem

Abstract This paper introduces meta-heuristics and its application to an employee transportation problem for a case study of a hard disk drive company. The objective of the development is to demonstrate improved route planning and fleet assignment to serve all employees in terms of cost savings. A GIS-based employee transportation system is created to design the shortest routes with feasible fleet allocation. The proposed meta-heuristics – central force optimization (CFO), chemical reaction optimization (CRO), and a parallel CFO-CRO – are compared with cuckoo search to validate the performance. The proposed algorithms can effectively determine the most feasible routes. The system is easy to use and capable of handling complex vehicle routing problems.