Improved solutions for the traveling purchaser problem

The traveling purchaser problem (TPP) is an interesting generalization of the well-known traveling salesman problem, in which a list of commodity items have to be purchased at some markets selling various commodities with different prices, and the total travel and purchase costs must be minimized. Applications include the purchase of raw materials for the manufacturing factories in which the total cost has to be minimized, and the scheduling of jobs over some machines with different set-up and job processing costs in which the total cost for completing the jobs has to be minimized. The TPP has been shown to be computationally intractable. Therefore, many heuristic solution procedures, including the Search algorithm, the Generalized-Savings algorithm, the Tour-Reduction algorithm, and the Commodity-Adding algorithm have been proposed to solve the TPP approximately. In this paper, we consider some variations of these algorithms to improve the solutions. The proposed variations are compared with the existing solution procedures. The results indicate that the proposed variations significantly improve the existing solutions.