The use of meta-heuristics to solve economic lot scheduling problem

Economic lot scheduling problem has been an important topic in production planning and scheduling research for more than four decades. The problem is known to be NP-hard due to it's combinatorial nature. In this paper, two meta-heuristics algorithms - Tabu Search and Simulated Annealing - are proposed. To investigate the effect of control parameters to the performance of tabu search and simulated annealing algorithms, a general factorial design of experiment study is used. Two Neighborhood Search heuristics that differ in rounding off scheme of the production frequencies are also tested. Experimental study shows that both tabu search and simulated annealing algorithms outperform two best known solution methods - Dobson's Heuristic and Hybrid Genetic Algorithm.