Three hybrid GAs for discounted fixed charge transportation problems

Abstract

The problem of allocating heterogeneous fleet of vehicles to the existing distribution network for dispensing products from a manufacturing firm to a set of depots is considered. It is assumed a heterogeneous fleet of vehicles with the given capacities and total costs consisting of a discounted fixed cost and a variable cost proportional to the amount shipped is employed for handling products. To minimize the total transportation costs, the problem is modeled in a form of the nonlinear mixed integer program. Due to the NP hard complexity of the mathematical model, three prioritized K-mean clustering hybrid GAs, by incorporating two new heuristic algorithms, are proposed. The efficiency of the algorithms is compared and the best one is designated. The designated algorithm is compared with CPLEX as well as two recently cited algorithms, and the results supported its high effectiveness and efficiency in terms of solution quality and CPU time.

Keywords

• manufacturing logistics
• prioritized k-mean clustering hybrid genetic algorithm
• fixed charge transportation model
• discounted transportation cost. milp model