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Productivity improvement through a sequencing generalised assignment in an assembly line system
Authors:Seyed-Esmaeil Moussavi  Morad Mahdjoub  Olivier Grunder
Affiliation:1. Nanomedicine lab, Univ. Bourgogne Franche-Comté, UTBM, Belfort, France.;2. ELLIADD Lab, Univ. Bourgogne Franche-Comté, UTBM, Montbéliard, France.
Abstract:This paper considers the assignment of heterogeneous workers to workstations of an assembly line in order to minimise the total production time. As the structure of the system implies that each of the workstations needs at least one worker, thus the problem can be considered as a generalised assignment problem (GAP). The objective is to perform an efficient human resource planning for a specified horizon consisting of several periods. Hence, we present an extension of the generalised assignment problem, consisting of a set of GAPs (one for each planning period) in which each GAP depends on the previous ones. A mixed integer mathematical model is presented for this sequencing assignment problem. The model is solved by an exact algorithm using Gurobi solver. It is proved that the problem is NP-hard and solving the medium and large size instances is not possible by the exact algorithms. Hence, two matheuristic approaches based on the disaggregated formulation of GAP are proposed. The first approach solves the problem through two sub-problems as the transportation formulation and assignment formulation. The second approach solves the problem by decomposition of the problem into several classical GAPs. The approaches are examined by a total of 27 instances. The results illustrate the efficiency of the proposed algorithms in the computational time and accuracy of the solutions.
Keywords:production cycle time  manpower planning  generalised assignment problem  matheuristic solving method  truck assembly line
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