scholarly journals A Self-adaptive Iterated Local Search Algorithm on the Permutation Flow Shop Scheduling Problem

2014 ◽  
Author(s):  
Xingye Dong ◽  
Maciek Nowak ◽  
Ping Chen ◽  
Youfang Lin
Keyword(s):  
Local Search ◽  
Flow Shop ◽  
Search Algorithm ◽  
Iterated Local Search ◽  
Flow Shop Scheduling ◽  
Scheduling Problem ◽  
Local Search Algorithm ◽  
Shop Scheduling ◽  
Permutation Flow Shop Scheduling ◽  
Permutation Flow Shop

Minimizing makespan and total flow time in permutation flow shop scheduling problems using modified gravitational emulation local search algorithm

2016 ◽  
Vol 232 (3) ◽  
pp. 534-545 ◽  
Author(s):  
R Sanjeev Kumar ◽  
KP Padmanaban ◽  
M Rajkumar
Keyword(s):  
Local Search ◽  
Flow Shop ◽  
Search Algorithm ◽  
Flow Shop Scheduling ◽  
Local Search Algorithm ◽  
Scheduling Problems ◽  
Total Flow ◽  
Shop Scheduling ◽  
Permutation Flow Shop Scheduling ◽  
Permutation Flow Shop

Permutation flow shop scheduling is a part of production scheduling problems. It allows “n” jobs to be processed on “m” machines. All the jobs are processed in all the machines, and the sequence of jobs being processed is the same in all the machines. It plays a vital role in both automated manufacturing industries and nondeterministic polynomial hard problem. Gravitational emulation local search algorithm is a randomization-based concept algorithm. It is used iteratively as the local search procedure for exploring the local optimum solution. Modified gravitational emulation local search algorithm is used for both exploring and exploiting the optimum solution for permutation flow shop scheduling problems. In this work, modified gravitational emulation local search algorithm is proposed to solve the permutation flow shop scheduling problems with the objectives such as minimization of makespan and total flow time. The computational results show that the performance solution of the proposed algorithm gives better results than the previous author’s approaches. Statistical tools are also used for finding out a relationship that exists between the two variables (makespan and total flow time) and to evaluate the performance of the proposed approach against the previous approaches in the literature.

A Parallel Iterated Local Search for Two-Agent Flow Shop Scheduling

2014 ◽  
Vol 926-930 ◽  
pp. 3476-3484 ◽  
Author(s):  
Xiao Qiang Xu ◽  
De Ming Lei
Keyword(s):  
Local Search ◽  
Flow Shop ◽  
Search Algorithm ◽  
Iterated Local Search ◽  
Flow Shop Scheduling ◽  
Local Search Algorithm ◽  
Shop Scheduling ◽  
Transition Mechanism ◽  
Neighborhood Structures ◽  
Agent Flow

In this paper a two-agent flow shop scheduling problem is studied and a simple parallel iterated local search algorithm is proposed to minimize the makespan of jobs from the first agent and the total tardiness of jobs from the second agent simultaneously. Parallelization is implemented by applying multiple independent searches, each of which uses three neighborhood structures with dynamical transition mechanism. The current solution of each independent search is replaced with a solution, which is randomly chosen from the non-dominated set and perturbed. The computational experiments show the promising advantage of the proposed method when compared to other algorithms of the problem.

Sign in / Sign up

Export Citation Format

Share Document