economic lot sizing and scheduling in distributed permutation flow shops

This paper addresses a new mixed integer nonlinear and linear mathematical programming economic lot sizing and scheduling problem in distributed permutation flow shop problem with number of identical factories and machines. different products must be distributed between the factories and then assignment of products to factories and sequencing of the products assigned to each factory has to be derived. the objective is to minimize the sum of setup costs, work-in-process inventory costs and finished products inventory costs per unit of time. since the proposed model is np-hard, an efficient water cycle algorithm is proposed to solve the model. to justify proposed wca, monarch butterfly optimization (mbo), genetic algorithm (ga) and combination of ga and simplex are utilized. in order to determine the best value of algorithms parameters that result in a better solution, a fine-tuning procedure according to response surface methodology is executed.