Remanufacturing planning with imprecise quality inputs through the goal programming and the satisfaction functions

In this paper, a tactical production-planning problem for remanufacturing is considered where inputs have different and imprecise quality levels. This situation is typical of most remanufacturing environment, where inputs are product returns (also called cores). Remanufacturing costs increase as the quality level decreases and any unused cores may be salvaged at a value that increases with their quality level. The aim of this paper is to develop a goal programming (GP) formulation within imprecise goals and inputs quality of product returns where the concept of satisfaction function will be utilised to introduce explicitly the manger’s preferences into the remanufacturing aggregate planning model. In order to verify our proposed model, a numerical example is described to generate the best satisfying aggregate plan.