Abstract: 〖WT5”BZ〗(1. School of Management, University of Shanghai for Science and Technology, Shanghai 200093, China;  2. Information Engineering Department, Weihai Vocational College, Weihai 264210, China;  3. School of Communications, Ludong University, Yantai 264025, China) It is known that the computational complexity in solving the integrated inventory-transportation optimization (ITIO) problem is exponential with the number of product types, the number of suppliers, and vehicle capacity. Thus, it is very difficult to obtain an optimal solution. To solve this problem, in view of different combinations of vehicle capacity (limited or unlimited) and shipping frequency (limited or unlimited) in many-to-one distribution network in the modern distribution logistics system, this problem is solved by using greedy randomized adaptive search procedure (GRASP) in this paper. It is a threestage method. At stage 1, distance ratio heuristic is applied to obtain an initial feasible solution. At stage 2, supplier assignment transfer algorithm is applied to search for the best solution in its neighborhood so as to improve the solutions obtained from stage 1. At stage 3, it repeats the procedure of stages 1 and 2 in an iterative way until a global best solution is achieved. Numerical experiments show that the proposed method can find a good solution with less computation. Also, the solution quality increases as the problem size increases.

Key words: inventory and transportation, integrated optimization, greedy randomized adaptive search procedure