Multi-Objective Optimization of Manufacturing Lot Size Under Stochastic Demand

In many manufacturing problems, multi-objective optimizations are representative models, as objectives considered a conflict with one another. real-life applications, optimizing specific solution concerning objective may end up in unacceptable results the other objectives. Many Manufacturing companies operate under uncertainties and this affects system performance. Stochastic product demand is of challenges faced by often system’s performance decision-making. Making proper decisions regarding lot-sizing problems critical for any manufacturer because it makes firm compete within market. paper, Markov chains conjunction stochastic goal programming were used to develop an optimization model lot size. The over-achievement or under-achievement size was determined defining constraints, deviation variables, priorities, function. different states represented chain. Using applied mathematics solver MATLAB TM, then solved, determining quantity be manufactured given quarter year changes from state