A ressource planner for hybrid assembly lines

This paper presents a new method to address the Hybrid Assembly Line Balancing Problem with multiple objectives. The aim is to assign a set of tasks to workstations and select the assembly equipment or resource to perform each of them. The goal is to minimize the total cost of the line by integrating design (congestion, machine real cost...) and operation issues (cycle time, precedence constraints and availability...). We used a Grouping Genetic Algorithm to tackle the problem, hybridized with an Branch & Cut and the multi-criteria decision-aid method Promethee. We present the optimization procedure that assigns tasks to workstations and selects assembly equipment for each workstation. The essential concepts adopted by the method are described. The first results of the algorithm are illustrated by a case study.

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