Balancing assembly lines operating with heterogeneous workers under uncertainty in task processing times

Abstract

Purpose

This paper considers the assembly line worker assignment and balancing problem of type-2 (ALWABP-2) with fuzzy task times. This problem is an extension of the (simple) SALBP-2 in which task times are worker-dependent and concurrently uncertain. Two criteria are simultaneously considered for minimization, namely, fuzzy cycle time and fuzzy smoothness index.

Design/methodology/approach

First, we show how fuzzy concepts can be used for managing uncertain task times. Then, we present a multiobjective genetic algorithm (MOGA) to solve the problem. MOGA is devoted to the search for Pareto-optimal solutions. For facilitating effective trade-off decision-making, two different MO approaches are implemented and tested within MOGA: a weighted-sum based approach and a Pareto-based approach.

Findings

Experiments over a set of fuzzified test problems show the effect of these approaches on the performance of MOGA while verifying its efficiency in terms of both solution and time quality.

Originality/value

To the author’s knowledge, no previous published work in the literature has studied the biobjective assembly line worker assignment and balancing problem of type-2 (ALWABP-2) with fuzzy task times.

Citation

Zacharia, P.T. and Nearchou, A.C. (2021), "Balancing assembly lines operating with heterogeneous workers under uncertainty in task processing times", Engineering Computations, Vol. 38 No. 10, pp. 3853-3878. https://doi.org/10.1108/EC-09-2020-0507