scholarly journals Batch Scheduling In A Two-Stage Flexible Flow Shop Problem

2014 ◽  
Vol 39 (1) ◽  
pp. 3-16 ◽  
Author(s):  
Enrique Gerstl ◽  
Gur Mosheiov ◽  
Assaf Sarig
Keyword(s):  
Flow Shop ◽  
Optimal Solution ◽  
Setup Time ◽  
Optimal Number ◽  
Two Stage ◽  
Second Stage ◽  
Flow Shop Problem ◽  
Batch Sizes ◽  
Batch Schedule ◽  
Identical Jobs

Abstract We study a special two-stage flexible flowshop, which consists of several parallel identical machines in the first stage and a single machine in the second stage. We assume identical jobs, and the option of batching, with a required setup time prior to the processing of a new batch. We also consider the option to use only a subset of the available machines. The objective is minimum makespan. A unique optimal solution is introduced, containing the optimal number of machines to be used, the sequence of batch sizes, and the batch schedule. The running time of our proposed solution algorithm is independent of the number of jobs, and linear in the number of machines

The Optimal Algorithm of a Two-Stage Flow Shop Problem with Infinite Number of Jobs

2011 ◽  
Vol 101-102 ◽  
pp. 290-293
Author(s):  
Qi Wei ◽  
Yong Wu
Keyword(s):  
Data Processing ◽  
Infinite Number ◽  
Flow Shop ◽  
Optimal Algorithm ◽  
Two Stage ◽  
Throughput Rate ◽  
Flow Shop Problem ◽  
Graphics Processing ◽  
Identical Jobs

In this paper, a two-machine two-stage flow shop with identical jobs is considered. Each of identical jobs has two tasks. The first task can be processed on either machine, called flexible task, while the second task must be processed on the second machine and can't be processed unless the first task has been processed. The problem is to determine the assignment of the flexible tasks to the machines for each job, with the objective of maximizing the throughput rate. This model is applied to the graphic programs processing which comprises data processing and graphics processing. We consider three cases regarding the capacity of the buffer between the machines with infinite number of jobs. We present optimal algorithm for each variant of the problem.

scholarly journals A two-stage flow shop scheduling with a critical machine and batch availability

2012 ◽  
Vol 37 (1) ◽  
pp. 39-56 ◽  
Author(s):  
Enrique Gerstl ◽  
Gur Mosheiov
Keyword(s):  
Flow Shop ◽  
Setup Time ◽  
Flow Shop Scheduling ◽  
Medium Size ◽  
Two Stage ◽  
Total Load ◽  
Time Dynamic ◽  
Second Stage ◽  
Processing Times ◽  
Critical Machine

AbstractWe study a two-stage flowshop, where each job is processed on the first (critical) machine, and then continues to one of two second-stage (dedicated) machines. We assume identical (but machine-dependent) job processing times. Jobs are processed on the critical machine in batches, and a setup time is required when starting a new batch. The setting assumes batch-availability, i.e., jobs become available for the second stage only when their entire batch is completed on the critical machine. We consider three objective functions: minimum makespan, minimum total load, and minimum weighted flow-time. Polynomial time dynamic programming algorithms are introduced, which are numerically shown to be able to solve problems of medium size in reasonable time. A heuristic for makespan minimization is presented and shown numerically to be both accurate and efficient.

A Heuristics Based on RA for Two-Stage Flexible Flow Shop Scheduling with Head Group Constraint

2011 ◽  
Vol 101-102 ◽  
pp. 783-789
Author(s):  
Zhan Tao Li ◽  
Qing Xin Chen ◽  
Ning Mao
Keyword(s):  
Flow Shop ◽  
Heuristic Method ◽  
Flow Shop Scheduling ◽  
Head Group ◽  
Start Time ◽  
Two Stage ◽  
Flexible Flow Shop ◽  
Shop Scheduling ◽  
Flow Shop Problem ◽  
Flexible Flow Shop Scheduling

Rapid access (RA) is an effective heuristic method for solving the permutation flow shop problem with the objective of makespan. This paper proposes a heuristic IRA (i.e., improved RA) for the two-stage flexible flow shop scheduling problem with head group constraint. In the heuristic IRA, two dispatch rules, i.e., earliest completion time first (ECT)) and earliest start time first (EST), are proposed for allocating devices for tasks. Benchmark testing results show that using ECT dispatch rule can significantly improve the performance of heuristic IRA. As comparison, the heuristic CDS and heuristic Palmer have also simulated under the same conditions, and the results show that the IRA is able to provide much better performance.

scholarly journals A two-stage hybrid flow shop problem with dedicated machine and release date

2018 ◽  
Vol 126 ◽  
pp. 214-223
Author(s):  
Zouhour Nabli ◽  
Soulef Khalfallah ◽  
Ouajdi Korbaa
Keyword(s):  
Flow Shop ◽  
Hybrid Flow Shop ◽  
Release Date ◽  
Two Stage ◽  
Flow Shop Problem

scholarly journals Minimizing the Makespan for a Two-Stage Three-Machine Assembly Flow Shop Problem with the Sum-of-Processing-Time Based Learning Effect

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Win-Chin Lin
Keyword(s):  
Learning Effect ◽  
Flow Shop ◽  
Optimal Solutions ◽  
Work Experiences ◽  
Two Stage ◽  
Processing Times ◽  
Production Environments ◽  
Flow Shop Problem ◽  
Iterated Greedy ◽  
Machine Assembly

Two-stage production process and its applications appear in many production environments. Job processing times are usually assumed to be constant throughout the process. In fact, the learning effect accrued from repetitive work experiences, which leads to the reduction of actual job processing times, indeed exists in many production environments. However, the issue of learning effect is rarely addressed in solving a two-stage assembly scheduling problem. Motivated by this observation, the author studies a two-stage three-machine assembly flow shop problem with a learning effect based on sum of the processing times of already processed jobs to minimize the makespan criterion. Because this problem is proved to be NP-hard, a branch-and-bound method embedded with some developed dominance propositions and a lower bound is employed to search for optimal solutions. A cloud theory-based simulated annealing (CSA) algorithm and an iterated greedy (IG) algorithm with four different local search methods are used to find near-optimal solutions for small and large number of jobs. The performances of adopted algorithms are subsequently compared through computational experiments and nonparametric statistical analyses, including the Kruskal–Wallis test and a multiple comparison procedure.

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