A smart algorithm for multi-criteria optimization of model sequencing problem in assembly lines

Abstract

Assembly Lines (ALs) are used for mass production as they offer lots of advantages over other production systems in terms of lead time and cost. The advent of mass customization has forced the manufacturing industries to update to Mixed-Model Assembly Lines (MMALs) but at the cost of increased complexity. In the real world, industries need to determine the sequence of models based on various conflicting performance measures/criteria. This paper investigates the Multi-Criteria Model Sequencing Problem (MC-MSP) using a modified simulation integrated Smart Multi-Criteria Nawaz, Enscore, and Ham (SMC-NEH) algorithm. To address the multiple criteria, a modified simulation integrated Smart Multi-Criteria Nawaz, Enscore, and Ham (SMC-NEH) algorithm was developed by integrating a priori approach with NEH algorithm. Discrete Event Simulation (DES) was used to evaluate each solution. A mathematical model was developed for three criteria: flow time, makespan and idle time. Further, to validate the effectiveness of the proposed SMC-NEH a case study and Taillard's benchmark instances were solved and a Multi-Criteria Decision-Making (MCDM) analysis was performed to compare the performance of the proposed SMC-NEH algorithm with the traditional NEH algorithm and its variants. The results showed that the proposed SMC-NEH algorithm outperformed the others in optimizing the conflicting multi-criteria problem.

Integrated Planning and Scheduling of Multiple Manufacturing Projects Under Resource Constraints Using Raccoon Family Optimization Algorithm

“…In this section, test instances from the previous section are solved by the proposed RFO algorithm along with ROA, ABC and GA. In literature, various techniques have been used to compare the performance of the algorithms, i.e., ARPD values [48], [57], convergence [48], ANOVA analysis [58] and robustness [48], [58]. Therefore, these techniques are selected as the performance metric for the comparison of the proposed RFO algorithm with the other above-mentioned algorithms.…”

A Multi-Objective Cuckoo Search Algorithm Based on the Record Matrix for a Mixed-Model Assembly Line Car-Sequencing Problem

“…In this paper, two optimization objectives are considered, including minimizing the total cost and time, as shown in equations (13) and (14). Equation (13) shows that the variation of parts usage rates, variation of workstation workload, and car model switching will be converted into the objective of minimizing the cost through the penalty cost unit and weighted coefficients, where ε and τ are penalty cost unit of the variation of parts usage rates M and workstation workload W respectively; α, φ, and γ are the weighted cost coefficients.…”

“…Reference [13] presented an integrated model to describe the asynchronous mixed-model assembly line combining balancing, sequencing, and buffer allocation. Reference [14] investigated the multi-criteria model sequencing problem, considering three factors: flow time, total duration, and idle time. An improved integrated smart multi-criterion Nawaz, Enscore, and Ham algorithm was presented to solve the problem.…”

Model for Integrating Production Scheduling and Maintenance Planning of Flow Shop Production System

“…However, the inclusion of genetic algorithms (GA), tabu search (TS), simulated annealing, and scatter methods, as a parts of the heuristic approach, may help in solving the problem by reaching its optimal solution. This type of approach for solving problems has been adopted to optimize Multi-Criteria Model Sequencing Problem (MC-MSP) of Mixed-Model Assembly Lines (MMALs) using a modified simulation integrated Smart Multi-Criteria Nawaz, Enscore, and Ham (SMC-NEH) algorithm [4]. Also, it has been applied to integrate planning and scheduling problem of multiple projects with different release dates and execution modes while considering the renewable and non-renewable resource constraints using raccoon family optimization (RFO) algorithm [5].…”