An uncertain furniture production planning problem with cumulative service levels

摘要: To investigate how the loss averse customer's psychological satisfaction affects company's furniture production planning, we establish a planning model under uncertain environment, where customer demand and costs are characterized by mutually independent variables. Based on prospect theory, about stockout performance is measured cumulative service levels in our model. In framework of uncertainty proposed can be transformed into an equivalent deterministic form. However, nonlinear mixed integer programming problem, which cannot solved conventional optimization algorithms. cope with this difficulty, chemical reaction algorithm integrated LINGO software designed to solve problem. order verify effectiveness hybrid (CRO) algorithm, conduct several numerical experiments via application example compare spanning tree-based genetic (hst-GA). The computational results show that CRO achieves better than hst-GA, also provide interesting managerial insights problems.