Knowledge Evolution Algorithm for Capacitated Lot Sizing Problem

The lot sizing problem is to find production quantities that will minimize the total setup cost, production cost and holding cost. Knowledge evolution algorithm for capacitated lot sizing problem was presented in this paper. A framework of knowledge evolution algorithm and the detailed realization of the algorithm were illustrated. The example of other literatures was computed. By comparison of the results, it can be found that knowledge evolution algorithm illustrated its higher searching efficiency and better stability than the genetic algorithm and the annealing penalty hybrid genetic algorithm of other literatures. Simulation results of the example demonstrated the effectiveness of this algorithm.