Multi-objective tabu search using a multinomial probability mass function

A tabu search approach to solve multi-objective combinatorial optimization problems is developed in this paper. This procedure selects an objective to become active for a given iteration with a multinomial probability mass function. The selection step eliminates two major problems of simple multi-objective methods, a priori weighting and scaling of objectives. Comparison of results on an NP-hard combinatorial problem with a previously published multi-objective tabu search approach and with a deterministic version of this approach shows that the multinomial approach is effective, tractable and flexible.

• Type: Journal
• Year: 2006
• Where: EOR
• Authors: Sadan Kulturel-Konak, Alice E. Smith, Bryan A. Norman
• Keywords: Combinatorial Optimization Problems, EOR 2006, Multinomial Probability Mass, Tabu Search Approach