In general, planning and scheduling of production are treated separately under the hierarchical strategy. Then, over the time, the iterative strategy appeared which partially considers the scheduling constraints during planning, except that the latter remains unsatisfactory because there is no guarantee that these constraints are taken into account. For this, is born the integrated strategy which integrates planning and scheduling and aims to solve the problem and define a feasible production plan. Since capacity constraints don’t reflect reality in terms of resource availability, and they are not always considered, capacity becomes aggregated. To remedy this problem, it is necessary to integrate more precise constraints of scheduling at the planning level. Based on this observation, we propose in this article a new model that integrates planning and scheduling and considers the constraint of resource availability. In our model, the objective function optimizes the total cost of production for a mono-level job-shop problem. To solve this N-P difficult problem we use a stochastic approached method as genetic algorithm (GA).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.