Abstract:

To improve the accuracy and efficiency of partner selection in the supply chain, we propose a hybrid algorithm of particle swarm and ant colony optimization (PSACO), establish a directed graph path model based on supply chain nodes and directed arcs, and construct a multiobjective optimization model. A discrete particle swarm optimization (DPSO) is modified so as to obtain initial solutions to the partner selection problem. Then the initial solutions are used to form pheromoneinitializing matrix for ant colony optimization (ACO), which is further modified by redefining its searching strategy to find the optimal solution. Experimental results demonstrate that the proposed PSACO algorithm can achieve more accurate solutions with greater efficiency, and is of better performance.

Key words: supply chain;partner selection;particle swarm optimization;ant colony algorithm