A MILP model for flexible job shop scheduling problem considering low flexibility

Production scheduling is a critical requirement in today’s production systems. The production scheduling problem focuses on the rational allocation of production resources, determining the processing order of production tasks and operations, satisfying production constraints arising from the product...

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Main Author: Liu, Minzheng
Other Authors: Ling Keck Voon
Format: Thesis-Master by Research
Language:English
Published: Nanyang Technological University 2024
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Online Access:https://hdl.handle.net/10356/175400
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spelling sg-ntu-dr.10356-1754002024-05-03T02:58:54Z A MILP model for flexible job shop scheduling problem considering low flexibility Liu, Minzheng Ling Keck Voon School of Electrical and Electronic Engineering EKVLING@ntu.edu.sg Engineering Flexible job shop scheduling Production scheduling is a critical requirement in today’s production systems. The production scheduling problem focuses on the rational allocation of production resources, determining the processing order of production tasks and operations, satisfying production constraints arising from the production environment such as the number of machines and task duration, and achieving optimal production goals, such as completing all tasks in the fastest way possible. The Flexible Job Shop Scheduling (FJSP) problem is a classical production scheduling issue, an extension of the Job Shop Scheduling (JSP) problem. The JSP problem involves allocating a set of jobs to a set of machines, where each job consists of multiple operations that must adhere to a precedence order. Each machine can process only one operation at a time for each job, and the time required for each operation on the corresponding machine is predetermined. The challenge in the JSP problem is to determine an appropriate order for processing operations or assignments, based on the production objective. FJSP represents a more complex and flexible variant of this problem, where at least one operation of a task can be performed on a set of alternative machines. Given that FJSP problems are NP-hard, solutions tend to be complex, varied, and often have limited applicability. Many FJSP scenarios require targeted modeling. In this paper, I propose a modeling approach for the static scheduling problem of job shops, considering low flexibility and demonstrating its usability by comparing it with other scheduling approaches, such as those based on genetic algorithm modeling. The paper is organized as follows:The first part of this paper offers a brief introduction to the FJSP problem, including background, research motivation, and main contributions, the second part provides a literature review,including a brief review and introduction of recent solutions to the FJSP problem, the third part describes a specific modeling approach, the fourth part details the test experiments and results of the modeling approach and includes comparisons with some other approaches, the fifth part analyzes the results from the fourth part and discusses the advantages and disadvantages of the modeling approach relative to others, and the sixth part concludes with a summary of findings and recommendations. Master's degree 2024-04-23T02:23:56Z 2024-04-23T02:23:56Z 2024 Thesis-Master by Research Liu, M. (2024). A MILP model for flexible job shop scheduling problem considering low flexibility. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175400 https://hdl.handle.net/10356/175400 10.32657/10356/175400 en This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
Flexible job shop scheduling
spellingShingle Engineering
Flexible job shop scheduling
Liu, Minzheng
A MILP model for flexible job shop scheduling problem considering low flexibility
description Production scheduling is a critical requirement in today’s production systems. The production scheduling problem focuses on the rational allocation of production resources, determining the processing order of production tasks and operations, satisfying production constraints arising from the production environment such as the number of machines and task duration, and achieving optimal production goals, such as completing all tasks in the fastest way possible. The Flexible Job Shop Scheduling (FJSP) problem is a classical production scheduling issue, an extension of the Job Shop Scheduling (JSP) problem. The JSP problem involves allocating a set of jobs to a set of machines, where each job consists of multiple operations that must adhere to a precedence order. Each machine can process only one operation at a time for each job, and the time required for each operation on the corresponding machine is predetermined. The challenge in the JSP problem is to determine an appropriate order for processing operations or assignments, based on the production objective. FJSP represents a more complex and flexible variant of this problem, where at least one operation of a task can be performed on a set of alternative machines. Given that FJSP problems are NP-hard, solutions tend to be complex, varied, and often have limited applicability. Many FJSP scenarios require targeted modeling. In this paper, I propose a modeling approach for the static scheduling problem of job shops, considering low flexibility and demonstrating its usability by comparing it with other scheduling approaches, such as those based on genetic algorithm modeling. The paper is organized as follows:The first part of this paper offers a brief introduction to the FJSP problem, including background, research motivation, and main contributions, the second part provides a literature review,including a brief review and introduction of recent solutions to the FJSP problem, the third part describes a specific modeling approach, the fourth part details the test experiments and results of the modeling approach and includes comparisons with some other approaches, the fifth part analyzes the results from the fourth part and discusses the advantages and disadvantages of the modeling approach relative to others, and the sixth part concludes with a summary of findings and recommendations.
author2 Ling Keck Voon
author_facet Ling Keck Voon
Liu, Minzheng
format Thesis-Master by Research
author Liu, Minzheng
author_sort Liu, Minzheng
title A MILP model for flexible job shop scheduling problem considering low flexibility
title_short A MILP model for flexible job shop scheduling problem considering low flexibility
title_full A MILP model for flexible job shop scheduling problem considering low flexibility
title_fullStr A MILP model for flexible job shop scheduling problem considering low flexibility
title_full_unstemmed A MILP model for flexible job shop scheduling problem considering low flexibility
title_sort milp model for flexible job shop scheduling problem considering low flexibility
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/175400
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