A Hybrid Reactive GRASP approach for the balancing of a mixed-model assembly line of type E with worker allocation

Abstract

To satisfy the changing requirements of the market, a manufacturer must be able to produce a large number of products in small quantities. This involves the simultaneous production of several models on a single production line, which is called a mixed-model assembly line (MiMAL). This study focuses on MiMALBP type E with worker allocation (MiMALBP-E-wa). The purpose of this study is to determine the best combination of workers (workstations) and cycle time to maximize line efficiency. To address this issue, a Hybrid Reactive Greedy Randomized Adaptive Search Procedure (HR-GRASP) has been developed.

To demonstrate the efficacy of HR-GRASP, an illustrative example is presented, in which eight workers are allocated between two models. Moreover, a comparison is made with another metaheuristic algorithm, the Genetic Algorithm (GA), to evaluate the proposed approach. The results demonstrate that the HR-GRASP method not only achieved maximum line efficiency but also converged more rapidly than the GA method.