Bi-objective scheduling for re-entrant hybrid flow shop with learning effect and setup times

Abstract

The production scheduling problem in hybrid flow shops is a complex combinatorial optimization problem observed in many real-world applications. The standard hybrid flow shop problem involves often unrealistic assumptions. In order to address the realistic assumptions, four additional traits were added to the proposed problem. These include re-entrant line, setup times, position-dependent learning effects, and the consideration of maximum completion time together with total tardiness as objective function. Since the proposed problem is non-deterministic polynomial-time (NP)-hard, a meta-heuristic algorithm is proposed as the solution procedure. The solution procedure is categorized as an a priori approach. To show the efficiency and effectiveness of the proposed algorithm, computational experiments were done on various test problems. Computational results show that the proposed algorithm can obtain an effective and appropriate solution quality for our investigated problem.

A novel bi-objective model for a job shop scheduling problem with consideration of Fuzzy parameters, modified learning effects and multiple preventive maintenance activities

“…They stated that different machines might exhibit different learning rates in practice. Vahedi Nouri et al [12], Amirian and Sahraean [13], Behnamian and Zandieh [14], Gao et al [15], and Mousavi et al [16], addressed the learning effects in the flow shop environment.…”

Hybrid Flow-Shop Scheduling Problems with Missing and Re-Entrant Operations Considering Process Scheduling and Production of Energy Consumption

“…Zhan et al [6] discussed the production scheduling problem derived from a real rotor workshop and solved it with a minimum delay. Mousavis et al [7] considered the setup time position-dependent learning effects and solved the maximum completion time and total delay as objective functions. Marichelvam et al [8] used a hybrid monkey search algorithm to optimize the total flow time, considering the maximum completion time.…”

A new mathematical formulation and a hybrid evolutionary algorithm for re-entrant flow-shop problem with release date

“…On the other hand, El-Khouly et al [33] and Moghaddam et al [34] addressed the MORFSS and modeled that to minimize other objectives such as costs, total completion, and utilization. As it is indicated in the list of papers, the multiobjective problem using different complex parameters has not been studied and only in a research by Mousavi [35] MORFSS is modeled using sequence dependent setup time. On the other hand, there is no study that concentrate on several objectives (more than two objectives) using release dates and due-dates.…”