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

Abstract

PurposeThis 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/approachFirst, 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.FindingsExperiments 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/valueTo 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.

Synergetic energy-conscious scheduling optimization of part feeding systems via a novel chaotic reference-guided policy

“…With respect to future research, we are inclined to apply synergy strategy to widespread engineering areas and extend the CRMSL to solve other kinds of realistic problems in manufacturing systems, such as assembly line balancing problem (Zacharia and Nearchou, 2021) or other constrained optimization problems (Kaveh et al, 2020). In addition, future work may involve more real-situation constraints in manufacturing environments.…”

Developments in the Literature and New Study Recommendations Within the Scope of the Assembly Line Worker Assignment and Balancing Problem (ALWABP)

“…Zacharia and Nearchou [49] argued that there is a tradeoff between C and smoothness index and that pareto solutions can be obtained. It first demonstrates how fuzzy concepts can be applied to the management of ambiguous task times.…”

“…Only a few studies have ever used this objective function ( [8,20,30,37,43,47,50]; Öksüz et al, 2017; [33]). In addition to that, [37] minimized C and operating costs; [47,48], and [49] evaluated the minimization of C and smoothness index simultaneously. 2019) and [24], using the probability values regarding the simultaneous cycle time and the case of temporary workers being assigned due to worker absenteeism, expressed two aims of minimization.…”