Heuristics for no-wait flow shop scheduling problem

Abstract

No-wait flow shop scheduling refers to continuous flow of jobs through different machines. The job once started should have the continuous processing through the machines without wait. This situation occurs when there is a lack of an intermediate storage between the processing of jobs on two consecutive machines. The problem of no-wait with the objective of minimizing makespan in flow shop scheduling is NP-hard; therefore the heuristic algorithms are the key to solve the problem with optimal solution or to approach nearer to optimal solution in simple manner. The paper describes two heuristics, one constructive and an improvement heuristic algorithm obtained by modifying the constructive one for sequencing n-jobs through m-machines in a flow shop under no-wait constraint with the objective of minimizing makespan. The efficiency of the proposed heuristic algorithms is tested on 120 Taillard's benchmark problems found in the literature against the NEH under no-wait and the MNEH heuristic for no-wait flow shop problem. The improvement heuristic outperforms all heuristics on the Taillard's instances by improving the results of NEH by 27.85%, MNEH by 22.56% and that of the proposed constructive heuristic algorithm by 24.68%. To explain the computational process of the proposed algorithm, numerical illustrations are also given in the paper. Statistical tests of significance are done in order to draw the conclusions.

No-Wait Flowshop Permutation Scheduling Problem : Fire Hawk Optimizer Vs Beluga Whale Optimization Algorithm

“…The first research data use the data in table 1 published by Nailwal et al (2016) with a problem of 5 jobs with 3 machines, referred to as Case 1 and belongs to the small data category. The second research data use Table 2 published by Carlier (1978) Car 06 with a problem of 8 jobs with 9 machines called Case 2 and belongs to the medium data category.…”

“…Rajendran (1994) proposed A No-wait Flowshop Scheduling Heuristic to minimize the makespan value. Nailwal, Gupta, and Jeet (2016) also proposed A heuristic for no-wait flow shop scheduling. In addition, some studies take an approach by applying new algorithms to solve the NWPFSP problem.…”

A Modified Mountain Gazelle Optimizer for Minimizing Energy Consumption on No-Wait Permutation Flow Shop Scheduling Problem

“…Meanwhile, essential metaheuristic algorithms are used in the no-wait flow shop scheduling problem [10]. This problem refers to the continuous flow of jobs through different machines, where jobs, once started, must have continuous processes [11]. Metaheuristic algorithms are widely used to tackle hard-to-solve optimization problems [12][13][14].…”

An Improved Discrete Migrating Birds Optimization Algorithm for the No-Wait Flow Shop Scheduling Problem

“…Many remarkable heuristic and metaheuristic algorithms have been proposed in the literature to optimize NWFSSP with the minimization of makespan, total flow time, and other objectives. Aldowaisan and Allahverdi [6], Laha and Chakraborty [7], Ye et al [8], and Nailwal et al [9] proposed heuristic and constructive heuristic algorithms to solve NWFSSP with the makespan criterion. In recent years, meta-heuristics, such as genetic algorithm (GA) by Seng et al [10], differential evolution (DE) algorithm by Qian et al [11], and variable neighborhood search (VNS) by Komaki and Malakooti [12], have been studied to solve the aforementioned problem.…”