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.

Solving Flow Shop Scheduling Problems with Blocking by using Genetic Algorithm

2019 ◽  
Vol 9 (2) ◽  
pp. 20-38
Author(s):  
Harendra Kumar ◽  
Pankaj Kumar ◽  
Manisha Sharma
Keyword(s):  
Genetic Algorithm ◽  
Completion Time ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Scheduling Problems ◽  
Working Process ◽  
Shop Scheduling ◽  
Mutation Operators ◽  
And Inversion ◽  
Present Algorithm

Flow shop scheduling problems have been analyzed worldwide due to their various applications in industry. In this article, a new genetic algorithm (NGA) is developed to obtain the optimum schedule for the minimization of total completion time of n-jobs in an m-machine flow shop operating without buffers. The working process of the present algorithm is very efficient to implement and effective to find the best results. To implement the proposed algorithm more effectively, similar job order crossover operators and inversion mutation operators have been used. Numerous examples are illustrated to explain proposed approach. Finally, the computational results indicate that present NGA performs much superior to the heuristics for blocking flow shop developed in the literature.

USING ANT COLONY OPTIMIZATION TO MINIMIZE THE FUZZY MAKESPAN AND TOTAL WEIGHTED FUZZY COMPLETION TIME IN FLOW SHOP SCHEDULING PROBLEMS

2009 ◽  
Vol 17 (04) ◽  
pp. 559-584 ◽  
Author(s):  
PENG-JEN LAI ◽  
HSIEN-CHUNG WU
Keyword(s):  
Completion Time ◽  
Ant Colony Algorithm ◽  
Fuzzy Numbers ◽  
Flow Shop ◽  
Computational Procedure ◽  
Ant Colony ◽  
Flow Shop Scheduling ◽  
Scheduling Problems ◽  
Shop Scheduling ◽  
Processing Times

The flow shop scheduling problems with fuzzy processing times are investigated in this paper. For some special kinds of fuzzy numbers, the analytic formulas of the fuzzy compltion time can be obtained. For the general bell-shaped fuzzy numbers, we present a computational procedure to obtain the approximated membership function of the fuzzy completion time. We define a defuzzification function to rank the fuzzy numbers. Under this ranking concept among fuzzy numbers, we plan to minimize the fuzzy makespan and total weighted fuzzy completion time. Because the ant colony algorithm has been successfully used to solve the scheduling problems with real-valued processing times, we shall also apply the ant colony algorithm to search for the best schedules when the processing times are assumed as fuzzy numbers. Numerical examples are also provided and solved by using the commercial software MATLAB.

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.

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.

Solving Flow Shop Scheduling Problems with Blocking by using Genetic Algorithm

2021 ◽  
pp. 1156-1174
Author(s):  
Harendra Kumar ◽  
Pankaj Kumar ◽  
Manisha Sharma
Keyword(s):  
Genetic Algorithm ◽  
Completion Time ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Scheduling Problems ◽  
Working Process ◽  
Shop Scheduling ◽  
Mutation Operators ◽  
And Inversion ◽  
Present Algorithm

Flow shop scheduling problems have been analyzed worldwide due to their various applications in industry. In this article, a new genetic algorithm (NGA) is developed to obtain the optimum schedule for the minimization of total completion time of n-jobs in an m-machine flow shop operating without buffers. The working process of the present algorithm is very efficient to implement and effective to find the best results. To implement the proposed algorithm more effectively, similar job order crossover operators and inversion mutation operators have been used. Numerous examples are illustrated to explain proposed approach. Finally, the computational results indicate that present NGA performs much superior to the heuristics for blocking flow shop developed in the literature.

A Heuristic Algorithm for Flow Shop Scheduling Problem

2014 ◽  
Vol 643 ◽  
pp. 374-379
Author(s):  
Hua Wei Yuan ◽  
Yuan Wei Jing ◽  
Tao Ren
Keyword(s):  
Heuristic Algorithm ◽  
Completion Time ◽  
Numerical Experiments ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Scheduling Problem ◽  
Shop Scheduling ◽  
Large Size ◽  
Flow Shop Problem ◽  
Weighted Completion Time

This paper considers the m-machine flow shop problem to minimize weighted completion time. A heuristic algorithm is presented to deal with the problem for large size problem. At the end of the paper, some numerical experiments show the effectiveness of the heuristic.

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