scholarly journals The Lagrangean Relaxation for the Flow Shop Scheduling Problem with Precedence Constraints, Release Dates and Delivery Times

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Marcelus Fabri ◽  
Helena Ramalhinho ◽  
Mauricio C. de Souza ◽  
Martin G. Ravetti
Keyword(s):  
Flow Shop ◽  
Mathematical Problem ◽  
Lagrangean Relaxation ◽  
Precedence Constraints ◽  
Flow Shop Scheduling ◽  
Computational Time ◽  
Release Dates ◽  
Delivery Times ◽  
Flow Shop Problem ◽  
Feasible Solutions

This work aims to present a methodology to support a company in the automotive business on scheduling the jobs on its final processes. These processes are: (i) checking the final product and (ii) loading the dispatch trucks. These activities are usually found in the outbound area of any manufacturing company. The problem faced is defined as the flow shop problem with precedence constraints, release dates, and delivery times. The major objective is to minimize the latest date a client receives its products. We present a time-indexed integer mathematical model to compute feasible solutions for the presented problem. Moreover, we take advantage of the Lagrangean Relaxation procedure to compute valid lower and upper bounds. The experiments were held based on the company’s premises. As a conclusion, the results showed that the methodology proposed was able to compute feasible solutions for all the instances tested. Also, the Lagrangean Relaxation approach was able to calculate better bounds in a shorter computational time than the Mathematical problem for the more complicated instances.

scholarly journals Optimal Results and Numerical Simulations for Flow Shop Scheduling Problems

2012 ◽  
Vol 2012 ◽  
pp. 1-9
Author(s):  
Tao Ren ◽  
Yuandong Diao ◽  
Xiaochuan Luo
Keyword(s):  
Local Search ◽  
Completion Time ◽  
Flow Shop ◽  
Asymptotic Optimality ◽  
Flow Shop Scheduling ◽  
Release Dates ◽  
Scheduling Problems ◽  
Improvement Strategy ◽  
Shop Scheduling ◽  
Flow Shop Problem

This paper considers them-machine flow shop problem with two objectives: makespan with release dates and total quadratic completion time, respectively. For Fm|rj|Cmax, we prove the asymptotic optimality for any dense scheduling when the problem scale is large enough. For Fm‖ΣCj2, improvement strategy with local search is presented to promote the performance of the classical SPT heuristic. At the end of the paper, simulations show the effectiveness of the improvement strategy.

Optimization of Two-Stage Hybrid Flow Shop Scheduling Problems Using Genetic Algorithm

2015 ◽  
Vol 766-767 ◽  
pp. 962-967
Author(s):  
M. Saravanan ◽  
S. Sridhar ◽  
N. Harikannan
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing Algorithm ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Computational Time ◽  
Hybrid Flow Shop ◽  
Scheduling Problems ◽  
Two Stage ◽  
Shop Scheduling ◽  
Hybrid Flow Shop Scheduling

The two-stage Hybrid flow shop (HFS) scheduling is characterized n jobs m machines with two-stages in series. The essential complexities of the problem need to solve the hybrid flow shop scheduling using meta-heuristics. The paper addresses two-stage hybrid flow shop scheduling problems to minimize the makespan time with the batch size of 100 using Genetic Algorithm (GA) and Simulated Annealing algorithm (SA). The computational results observed that the GA algorithm is finding out good quality solutions than SA with lesser computational time.

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 The Discrete Particle Swarm Optimization Algorithms For Permutation Flowshop Scheduling Problem

2019 ◽  
Vol 20 (2) ◽  
pp. 105
Author(s):  
Ikhlasul Amallynda
Keyword(s):  
Particle Swarm Optimization ◽  
Flow Shop ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Flow Shop Scheduling ◽  
Computational Time ◽  
Scheduling Problem ◽  
Discrete Particle Swarm Optimization ◽  
Swarm Optimization ◽  
Discrete Particle

In this paper, two types of discrete particle swarm optimization (DPSO) algorithms are presented to solve the Permutation Flow Shop Scheduling Problem (PFSP). We used criteria to minimize total earliness and total tardiness. The main contribution of this study is a new position update method is developed based on the discrete domain because PFSP is represented as discrete job permutations. In addition, this article also comes with a simple case study to ensure that both proposed algorithm can solve the problem well in the short computational time. The result of Hybrid Discrete Particle Swarm Optimization (HDPSO) has a better performance than the Modified Particle Swarm Optimization (MPSO). The HDPSO produced the optimal solution. However, it has a slightly longer computation time. Besides the population size and maximum iteration have any impact on the quality of solutions produced by HDPSO and MPSO algorithms 

One-machine sequencing with release dates, delivery times and precedence constraints

1988 ◽  
Vol 20 (4) ◽  
pp. 483-490
Author(s):  
A. Adrabiński ◽  
J. Grabowski ◽  
M. Wodecki
Keyword(s):  
Precedence Constraints ◽  
Release Dates ◽  
Delivery Times ◽  
One Machine

GA-BASED IMPROVEMENT HEURISTIC FOR MINIMIZING MAKESPAN IN A GENERAL FLOW-SHOP SCHEDULING PROBLEM

2021 ◽  
pp. 1109-1115
Author(s):  
Brahma Datta Shukla, Pragya Singh Tomar
Keyword(s):  
Lower Bound ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Scheduling Problem ◽  
Shop Scheduling ◽  
General Flow ◽  
Constructive Heuristic ◽  
Permutation Flow Shop ◽  
Constructive Heuristics ◽  
Flow Shop Problem

The study proposes an evolutionary algorithm-based improvement heuristic for the permutation flow-shop problem. The method uses a constructive heuristic to arrive at a good first solution. The GA-based improvement heuristic is used in conjunction with CDS, Gupta's algorithm, and Palmer's Slope Index, which are all well-known constructive heuristics. The method is put to the test on a series of ten issues that vary from 4 to 25 tasks and 4 to 30 machines. The outcomes are also compared to some of the most well-known lower-bound options

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