USING GENETIC ALGORITHMS TO SOLVE FUZZY FLOW SHOP SCHEDULING PROBLEMS BASED ON POSSIBILITY AND NECESSITY MEASURES

2008 ◽  
Vol 16 (03) ◽  
pp. 409-433 ◽  
Author(s):  
PENG-JEN LAI ◽  
HSIEN-CHUNG WU
Keyword(s):  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Fuzzy Sets Theory ◽  
Scheduling Problems ◽  
Due Dates ◽  
Objective Functions ◽  
Earliness And Tardiness ◽  
Processing Times ◽  
Fuzzy Processing Times ◽  
Sets Theory

The scheduling problems with fuzzy processing times and fuzzy due dates are investigated in this paper. The concepts of earliness and tardiness are interpreted by using the concepts of possibility and necessity measures that were developed in fuzzy sets theory. Many types of objective function will be taken into account through the different combinations of possibility and necessity measures. The purpose of this paper is to obtain the optimal schedules based on these objective functions. The genetic algorithm will be invoked to tackle these objective functions. Four numerical examples are also provided and solved by using the commercial software MATLAB.

An effective method for solving flow shop scheduling problems with fuzzy processing times

1993 ◽  
Vol 25 (1-4) ◽  
pp. 239-242 ◽  
Author(s):  
Yasuhiro Tsujimura ◽  
Seung Hun Park ◽  
In Seong Chang ◽  
Mitsuo Gen
Keyword(s):  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Scheduling Problems ◽  
Shop Scheduling ◽  
Processing Times ◽  
Fuzzy Processing Times

Two-Machine Ordered Flow Shop Scheduling with Generalized Due Dates

2020 ◽  
Vol 37 (01) ◽  
pp. 1950032
Author(s):  
Myoung-Ju Park ◽  
Byung-Cheon Choi ◽  
Yunhong Min ◽  
Kyung Min Kim
Keyword(s):  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Due Dates ◽  
Shop Scheduling ◽  
Processing Times ◽  
Specific Position ◽  
Polynomially Solvable ◽  
Definition Of ◽  
Tardy Jobs ◽  
Np Hardness

We consider a two-machine flow shop scheduling with two properties. The first is that each due date is assigned for a specific position different from the traditional definition of due dates, and the second is that a consistent pattern exists in the processing times within each job and each machine. The objective is to minimize maximum tardiness, total tardiness, or total number of tardy jobs. We prove the strong NP-hardness and inapproximability, and investigate some polynomially solvable cases. Finally, we develop heuristics and verify their performances through numerical experiments.

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 Solving Constrained Flow-Shop Scheduling Problem through Multistage Fuzzy Binding Approach with Fuzzy Due Dates

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Hamiden Abd El-Wahed Khalifa ◽  
Sultan S. Alodhaibi ◽  
Pavan Kumar
Keyword(s):  
Fuzzy Numbers ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Due Dates ◽  
Optimal Sequence ◽  
Elapsed Time ◽  
Processing Times ◽  
Scheduling Model ◽  
Interval Approximation ◽  
Real World Problems

This paper deals with constrained multistage machines flow-shop (FS) scheduling model in which processing times, job weights, and break-down machine time are characterized by fuzzy numbers that are piecewise as well as quadratic in nature. Avoiding to convert the model into its crisp, the closed interval approximation for the piecewise quadratic fuzzy numbers is incorporated. The suggested method leads a noncrossing optimal sequence to the considered problem and minimizes the total elapsed time under fuzziness. The proposed approach helps the decision maker to search for applicable solution related to real-world problems and minimizes the total fuzzy elapsed time. A numerical example is provided for the illustration of the suggested methodology.

A Note on Flow Shop Scheduling with the Effects of Learning and Deterioration

2014 ◽  
Vol 513-517 ◽  
pp. 2149-2152
Author(s):  
Yu Ping Niu ◽  
Ji Bo Wang
Keyword(s):  
Learning Effect ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Scheduling Problems ◽  
Shop Scheduling ◽  
Processing Times ◽  
Polynomially Solvable ◽  
Machine Scheduling Problems ◽  
Completion Times ◽  
Sum Of Completion Times

In this note, we consider the machine scheduling problems with the effects of learning and deterioration. In this model, job processing times are defined by functions dependent on their starting times and positions in the sequence. The scheduling objectives are makespan, sum of completion times. It is shown that even with the introduction of learning effect and deterioration jobs to job processing times, several flow shop problems remain polynomially solvable.

A Note on Scheduling Jobs with Extended Sum-of-Processing-Times-Based and Position-Based Learning Effect

2015 ◽  
Vol 32 (02) ◽  
pp. 1550001 ◽  
Author(s):  
Yu-Ping Niu ◽  
Long Wan ◽  
Ji-Bo Wang
Keyword(s):  
Learning Effect ◽  
Flow Shop ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Flow Shop Scheduling ◽  
Scheduling Problems ◽  
Processing Times ◽  
Effect Model ◽  
Special Cases ◽  
Machine Scheduling Problems

The note deals with machine scheduling problems with a more general learning effect model, i.e., the actual job processing time is a function of the sum of the function of the processing times of the jobs already processed and job position. We show that some single machine scheduling problems are still polynomially solvable under the proposed model. We also show that some special cases of the flow shop scheduling problems can be solved in polynomial time.

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