Equal size lot streaming to job-shop scheduling problem using genetic algorithms

Tung Sun Chan; T. C. Wong; P. L.Y. Chan

Equal size lot streaming to job-shop scheduling problem using genetic algorithms

Tung Sun Chan, T. C. Wong, P. L.Y. Chan

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

22 Citations (Scopus)

Abstract

A novel approach to solve Equal Size Lot Streaming (ESLS) in Job-shop Scheduling Problem (JSP) using Genetic Algorithms (GAs) is proposed. LS refers to a situation that a lot can be split into a number of smaller lots (or sub-lots) so that successive operation can be overlapped. By adopting the proposed approach, the sub-lot number for different lots and the processing sequence of all sub-lots can be determined simultaneously using GAs. Applying Just-In-Time (JIT) policy, the results show that the solution can minimize both the overall penalty cost and total setup time with the development of multi-objective function. In this connection, decision makers can then assign various weightings so as to enhance the reliability of the final solution.

Original language	English
Title of host publication	IEEE International Symposium on Intelligent Control - Proceedings
Pages	472-476
Number of pages	5
Publication status	Published - 1 Dec 2004
Externally published	Yes
Event	Proceedings of the 2004 IEEE International Symposium on Intelligent Control - 2004 ISIC - Taipei, Taiwan Duration: 2 Sept 2004 → 4 Sept 2004

Conference

Conference	Proceedings of the 2004 IEEE International Symposium on Intelligent Control - 2004 ISIC
Country/Territory	Taiwan
City	Taipei
Period	2/09/04 → 4/09/04

ASJC Scopus subject areas

Control and Systems Engineering
Modelling and Simulation
Computer Science Applications
Electrical and Electronic Engineering

Cite this

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title = "Equal size lot streaming to job-shop scheduling problem using genetic algorithms",

abstract = "A novel approach to solve Equal Size Lot Streaming (ESLS) in Job-shop Scheduling Problem (JSP) using Genetic Algorithms (GAs) is proposed. LS refers to a situation that a lot can be split into a number of smaller lots (or sub-lots) so that successive operation can be overlapped. By adopting the proposed approach, the sub-lot number for different lots and the processing sequence of all sub-lots can be determined simultaneously using GAs. Applying Just-In-Time (JIT) policy, the results show that the solution can minimize both the overall penalty cost and total setup time with the development of multi-objective function. In this connection, decision makers can then assign various weightings so as to enhance the reliability of the final solution.",

author = "Chan, \{Tung Sun\} and Wong, \{T. C.\} and Chan, \{P. L.Y.\}",

year = "2004",

month = dec,

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language = "English",

pages = "472--476",

booktitle = "IEEE International Symposium on Intelligent Control - Proceedings",

note = "Proceedings of the 2004 IEEE International Symposium on Intelligent Control - 2004 ISIC ; Conference date: 02-09-2004 Through 04-09-2004",

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T1 - Equal size lot streaming to job-shop scheduling problem using genetic algorithms

AU - Chan, Tung Sun

AU - Wong, T. C.

AU - Chan, P. L.Y.

PY - 2004/12/1

Y1 - 2004/12/1

N2 - A novel approach to solve Equal Size Lot Streaming (ESLS) in Job-shop Scheduling Problem (JSP) using Genetic Algorithms (GAs) is proposed. LS refers to a situation that a lot can be split into a number of smaller lots (or sub-lots) so that successive operation can be overlapped. By adopting the proposed approach, the sub-lot number for different lots and the processing sequence of all sub-lots can be determined simultaneously using GAs. Applying Just-In-Time (JIT) policy, the results show that the solution can minimize both the overall penalty cost and total setup time with the development of multi-objective function. In this connection, decision makers can then assign various weightings so as to enhance the reliability of the final solution.

AB - A novel approach to solve Equal Size Lot Streaming (ESLS) in Job-shop Scheduling Problem (JSP) using Genetic Algorithms (GAs) is proposed. LS refers to a situation that a lot can be split into a number of smaller lots (or sub-lots) so that successive operation can be overlapped. By adopting the proposed approach, the sub-lot number for different lots and the processing sequence of all sub-lots can be determined simultaneously using GAs. Applying Just-In-Time (JIT) policy, the results show that the solution can minimize both the overall penalty cost and total setup time with the development of multi-objective function. In this connection, decision makers can then assign various weightings so as to enhance the reliability of the final solution.

UR - https://www.scopus.com/pages/publications/20344394416

M3 - Conference article published in proceeding or book

SP - 472

EP - 476

BT - IEEE International Symposium on Intelligent Control - Proceedings

T2 - Proceedings of the 2004 IEEE International Symposium on Intelligent Control - 2004 ISIC

Y2 - 2 September 2004 through 4 September 2004

ER -

Equal size lot streaming to job-shop scheduling problem using genetic algorithms

Abstract

Conference

ASJC Scopus subject areas

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