scholarly journals A Local Search Algorithm for the Flow Shop Scheduling Problem with Release Dates

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Tao Ren ◽  
Meiting Guo ◽  
Lin Lin ◽  
Yunhui Miao
Keyword(s):  
Local Search ◽  
Flow Shop ◽  
Search Algorithm ◽  
Flow Shop Scheduling ◽  
Release Dates ◽  
Scheduling Problem ◽  
Local Search Algorithm ◽  
High Quality ◽  
Shop Scheduling ◽  
Simulation Results

This paper discusses the flow shop scheduling problem to minimize the makespan with release dates. By resequencing the jobs, a modified heuristic algorithm is obtained for handling large-sized problems. Moreover, based on some properties, a local search scheme is provided to improve the heuristic to gain high-quality solution for moderate-sized problems. A sequence-independent lower bound is presented to evaluate the performance of the algorithms. A series of simulation results demonstrate the effectiveness of the proposed algorithms.

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.

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.

An Iterated Local Search Algorithm for the Lot-Streaming Flow Shop Scheduling Problem

2014 ◽  
Vol 31 (06) ◽  
pp. 1450045 ◽  
Author(s):  
Hongyan Sang ◽  
Liang Gao ◽  
Xinyu Li
Keyword(s):  
Local Search ◽  
Flow Shop ◽  
Search Algorithm ◽  
Iterated Local Search ◽  
Flow Shop Scheduling ◽  
Scheduling Problem ◽  
Lot Streaming ◽  
Acceptance Criterion ◽  
Shop Scheduling ◽  
Streaming Flow

The lot-streaming flow shop scheduling problem plays an important role in modern industry. This paper addresses this problem with the objective of minimizing the total weighted earliness and tardiness penalties and then proposes a simple but effective iterated local search (ILS) algorithm. In the proposed ILS algorithm, an adapted Nawaz–Enscore–Ham (NEH) heuristic is used to generate an initial solution. A local search procedure based on the insertion neighborhood is employed to perform local exploitation. A simulated-annealing-typed acceptance criterion is utilized to determine the start point for next iteration. Extensive experiments are conducted to compare the proposed ILS algorithm with some existing algorithms. The computational results and comparisons demonstrate the effectiveness of the proposed ILS algorithm.

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