A Hybrid approach for the Mixed-Model Assembly Line Balancing problem Type-II

Mixed-model assembly lines are used by manufacturers to produce different models of one product to meet the diversity of customer demands without changing the configuration of the assembly line, models are produced in an intermixed sequence, and the needed time to produce one model is known by the cycle time. Minimizing the cycle time is an important issue by which the production rate of the mixed-model assembly line can be maximized, thus in the step of designing the new assembly line, a famous problem must be solve known in the literature by the mixed-model assembly line balancing problem type-II (MiMALBP-II) that aims to find a minimum average cycle time taken in consideration all models to be produced in the assembly line. In this paper, we propose a hybrid algorithm that combines the Reactive Greedy Randomized Adaptive Search Procedure (Reactive GRASP) and the Ranked Positional Weight (RPW) heuristic to solve MiMALBP-II. The proposed algorithm is tested on three problems and obtained results are compared with those obtained by the basic GRASP.