Threshold accepting framework for discrete and continuous search spaces. (14th June 2010) - Dhouib, Souhail
In this paper, a threshold accepting multi-agents (TA-MA) framework is proposed to optimise discrete and continuous problems. The TA-MA framework uses two agents, in each one a threshold accepting (TA) metaheuristic is started with different initial parameters. The cooperation between these agents is assured by an adaptive memory named taboo central memory (TCM). Computational experiments, on the single machine total weighted tardiness (SMTWT) problems and on two engineering design optimisation problems (the supported I-beam and the machine tool spindle), show that the proposed TA-MA algorithm can obtain the optimal solution or much better than the best known one for all standard benchmark problems instances from the literature.