Random move tabu search for freight proportion allocation problem

We study a freight proportion allocation problem (FPAP), which is a kind of transportation problem faced by MG, one of the world's leading grocery retailers. MG has a large quantity of freight for carriers to ship to Europe. During the process of freight allocation, the shipper must consider three constraints, which are minimum quantity commitment (MQC), quantity limit per carrier and cost balance among sales divisions. With these constraints, the FPAP becomes computationally intractable. By incorporating random move subroutine, we devised a special tabu search procedure to solve this problem. Different from classical tabu search who usually runs in the feasible regions, random move tabu search enables the search process to enter into infeasible regions and visit disjointed feasible regions. Extensive experiments have been conducted to measure the performance of our proposed tabu search and CPLEX solver and have shown that the random move tabu search behaves better.