scholarly journals Two Stage Flow Shop Scheduling Model Including Transportation Time with Equipotential Machines at Every Stage

2019 ◽  
Vol 8 (12) ◽  
pp. 5090-5094
Keyword(s):  
Processing Time ◽  
Parallel Machines ◽  
Flow Shop ◽  
Solution Algorithm ◽  
Flow Shop Scheduling ◽  
Two Stage ◽  
Transportation Time ◽  
Shop Scheduling ◽  
Scheduling Model ◽  
Two Machines

This study presents a solution algorithm for the problem of minimizing the makespan on equipotential parallel machines at every stage in two stage flow shop scheduling model. The processing time of all the jobs on all the two machines is given and the time for which parallel equipotential machines are available is also given. Transportation time for moving the jobs from first machine to second machine is also taken into consideration. A mathematical illustration is also given in support of the algorithm proposed

Flexible flow shop scheduling with interval grey processing time

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yuquan Wang ◽  
Naiming Xie
Keyword(s):  
Processing Time ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Scheduling Problems ◽  
Flexible Flow Shop ◽  
Content Type ◽  
Shop Scheduling ◽  
Scheduling Model ◽  
Grey Number ◽  
Flexible Flow Shop Scheduling

Purposepurpose of this paper is providing a solution for flexible flow shop scheduling problem with uncertain processing time in aeronautical composite lay-up workshop.Design/methodology/approachA flexible flow scheduling model and algorithm with interval grey processing time is established. First, according to actual needs of composite laminate shop scheduling process, interval grey number is used to represent uncertain processing time, and interval grey processing time measurement method, grey number calculation and comparison rules, grey Gantt chart, and other methods are further applied. Then a flexible flow shop scheduling model with interval grey processing time (G-FFSP) is established, and an artificial bee colony algorithm based on an adaptive neighbourhood search strategy is designed to solve the model. Finally, six examples are generated for simulation scheduling, and the efficiency and performance of the model and algorithm are evaluated by comparing the results.FindingsResults show that flexible flow shop scheduling model and algorithm with interval grey processing time can provide an optimal solution for composite lay-up shop scheduling problems and other similar flow shop scheduling problems.Social implicationsUncertain processing time is common in flexible workshop manufacturing, and manual scheduling greatly restricts the production efficiency of workshop. In this paper, combined with grey system theory, an intelligent algorithm is used to solve flexible flow shop scheduling problem to promote intelligent and efficient production of enterprises.Originality/valueThis paper applies and perfects interval grey processing time measurement method, grey number calculation and comparison rules, grey Gantt chart and other methods. A flexible flow shop scheduling model with interval grey processing time is established, and an artificial bee colony algorithm with an adaptive domain search strategy is designed. It provides a comprehensive solution for flexible flow shop scheduling with uncertain processing time.

Evaluation Dispatching Rules for Two-Stage Hybrid Flow Shop Scheduling with Parallel Machines

2012 ◽  
Vol 152-154 ◽  
pp. 1487-1491
Author(s):  
Parinya Kaweegitbundit
Keyword(s):  
Processing Time ◽  
Parallel Machines ◽  
Flow Shop ◽  
Total Tardiness ◽  
Flow Shop Scheduling ◽  
Dispatching Rules ◽  
Hybrid Flow Shop ◽  
Two Stage ◽  
Identical Parallel Machine ◽  
Hybrid Flow Shop Scheduling

This paper considers two stage hybrid flow shop with identical parallel machine and evaluate performance of common dispatching rules; shortage processing time (SPT) longest processing time (LPT) earliness due date (EDD) and first in first out (FIFO). The objectives are to determine makespan and total tardiness have been minimized. To evaluated performance of dispatching rules, the results have been compared on each criterion. The experimental results show that SPT outperform than other rules with minimizes makespan as an objective function for all problems. On the other hand, for minimize total tardiness as an objective. The EDD rule outperform than other rules.

scholarly journals Solving no-wait two-stage flexible flow shop scheduling problem with unrelated parallel machines and rework time by the adjusted discrete Multi Objective Invasive Weed Optimization and fuzzy dominance approach

2017 ◽  
Vol 10 (5) ◽  
pp. 887 ◽  
Author(s):  
Hassan Jafarzadeh ◽  
Nazanin Moradinasab ◽  
Ali Gerami
Keyword(s):  
Parallel Machines ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Scheduling Problem ◽  
Two Stage ◽  
Flexible Flow Shop ◽  
Shop Scheduling ◽  
Multi Objective ◽  
No Wait ◽  
Flexible Flow Shop Scheduling

Purpose: Adjusted discrete Multi-Objective Invasive Weed Optimization (DMOIWO) algorithm, which uses fuzzy dominant approach for ordering, has been proposed to solve No-wait two-stage flexible flow shop scheduling problem.Design/methodology/approach: No-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times and probable rework in both stations, different ready times for all jobs and rework times for both stations as well as unrelated parallel machines with regards to the simultaneous minimization of maximum job completion time and average latency functions have been investigated in a multi-objective manner. In this study, the parameter setting has been carried out using Taguchi Method based on the quality indicator for beater performance of the algorithm.Findings: The results of this algorithm have been compared with those of conventional, multi-objective algorithms to show the better performance of the proposed algorithm. The results clearly indicated the greater performance of the proposed algorithm.Originality/value: This study provides an efficient method for solving multi objective no-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times, probable rework in both stations, different ready times for all jobs, rework times for both stations and unrelated parallel machines which are the real constraints.

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