research-article

Introduction to A Compromise Programming Based Method for Complex Scheduling and Planning Problems

Authors:

Jafreezal Jaafar,

Izzatdin Abdul Aziz, and

Giang Hoang NguyenAuthors Info & Claims

IMMS '21: Proceedings of the 4th International Conference on Information Management and Management Science

August 2021

Pages 265 - 272

https://doi.org/10.1145/3485190.3485231

Published: 02 December 2021 Publication History

Abstract

Planning and Planning (SP) plays a vital role in many fields. However, SP problems become more complex when they require to archive multi goals in decision-making processes that are more difficult to solve and push the decision-maker into a dilemma. This paper introduces an adaptive method based on the compromise programming approach to multi-objective optimization (MOP) in scheduling and planning (SP) problems. The proposed method gives an effective integration of mathematical programming with evolutionary algorithms (EA). Through the technique, decision-makers can validate the models as well as evaluate different decision alternatives. The method is in the development progress. However, we have obtained preliminary results by applying the method for solving some SP problems. These results show the feasibility of the proposed method.

References

[1]

J. Blazewicz, K. H. Ecker, E. Pesch, G. Schmidt, M. Sterna, and J. Weglarz, Handbook on Scheduling. Cham: Springer International Publishing, 2019.

[2]

M. Padberg, “Combinatorial Optimization: An Introduction,” 1999.

[3]

N. Gunantara and N. P. Sastra, “Cooperative Diversity Selection Protocol Using Pareto Method with Multi Objective Criterion in Wireless Ad Hoc Networks,” Int. J. Multimed. Ubiquitous Eng., vol. 11, no. 5, pp. 43–54, May 2016.

[4]

T. Chugh, K. Sindhya, J. Hakanen, and K. Miettinen, “A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms,” Soft Comput., vol. 23, no. 9, pp. 3137–3166, May 2019.

Digital Library

[5]

J. R. Meredith, “Reconsidering the Philosophical Basis of OR/MS,” Oper. Res., vol. 49, no. 3, pp. 325–333, Jun. 2001, [Online]. Available: http://www.jstor.org/stable/3088630.

[6]

P. Taillandier and J. Gaffuri, “Objective Function Designing Led by User Preferences Acquisition,” CoRR, vol. abs/1204.4, 2012, [Online]. Available: http://arxiv.org/abs/1204.4990.

[7]

R. N. Monemi, S. Gelareh, A. Nagih, and D. Jones, “Bi-objective load balancing multiple allocation hub location: a compromise programming approach,” Ann. Oper. Res., vol. 296, no. 1–2, Jan. 2021.

[8]

T. S. Ngo, “Some Algorithms to Solve a Bi-Objectives Problem for Team Selection,” Appl. Sci., vol. 10, no. 8, Apr. 2020.

[9]

Ngo Tung Son, Le Van Thanh, Tran Binh Duong, and Bui Ngoc Anh. 2018. A decision support tool for cross-functional team selection: case study in ACM-ICPC team selection. In Proceedings of the 2018 International Conference on Information Management & Management Science (IMMS '18). Association for Computing Machinery, New York, NY, USA, 133–138.

Digital Library

[10]

M. Koppen and K. Yoshida, “Visualization of Pareto-Sets in Evolutionary Multi-Objective Optimization,” Sep. 2007.

[11]

M. López-Ibáñez, L. Paquete, and T. Stützle, “Exploratory Analysis of Stochastic Local Search Algorithms in Biobjective Optimization,” in Experimental Methods for the Analysis of Optimization Algorithms, Berlin, Heidelberg: Springer Berlin Heidelberg, 2010.

[12]

F. Kudo and T. Yoshikawa, “Knowledge extraction in multi-objective optimization problem based on visualization of Pareto solutions,” Jun. 2012.

[13]

S. T. Ngo, J. Jaafar, I. A. Aziz, and B. N. Anh, “A Compromise Programming for Multi-Objective Task Assignment Problem,” Computers, vol. 10, no. 2, Jan. 2021.

[14]

N. T. Son, J. Jaafar, I. A. Aziz, and B. N. Anh, “Meta-Heuristic Algorithms for Learning Path Recommender at MOOC,” IEEE Access, vol. 9, pp. 59093–59107, 2021.

[15]

S. T. Ngo, J. B. Jaafar, I. A. Aziz, G. H. Nguyen, and A. N. Bui, “Genetic Algorithm for Solving Multi-Objective Optimization in Examination Timetabling Problem,” Int. J. Emerg. Technol. Learn., vol. 16, no. 11, p. 4, Jun. 2021.

[16]

Son Tung Ngo, Jaafar Jafreezal, Giang Hoang Nguyen, and Anh Ngoc Bui. 2021. A Genetic Algorithm for Multi-Objective Optimization in Complex Course Timetabling. In 2021 10th International Conference on Software and Computer Applications (ICSCA 2021). Association for Computing Machinery, New York, NY, USA, 229–237.

Digital Library

[17]

Son, N. T., Jaafar, J., Aziz, I. A., Anh, B. N., Binh, H. D. (2021). A Compromise Programming to Task Assignment Problem in Software Development Project. CMC-Computers, Materials & Continua, 69(3), 3429–3444.

Cited By

Son NNguyet Ha TJAAFAR JAnh BGiang T(2023)Some Metaheuristics for Tourist Trip Design Problem2023 IEEE Symposium on Industrial Electronics & Applications (ISIEA)10.1109/ISIEA58478.2023.10212154(1-10)Online publication date: 15-Jul-2023
https://doi.org/10.1109/ISIEA58478.2023.10212154
Ngo SJaafar JIzzatdin ATong GBui A(2022)Some metaheuristic algorithms for solving multiple cross-functional team selection problemsPeerJ Computer Science10.7717/peerj-cs.10638(e1063)Online publication date: 9-Aug-2022
https://doi.org/10.7717/peerj-cs.1063
Ngo TJaafar JAziz IAftab MNguyen HBui N(2022)Metaheuristic Algorithms Based on Compromise Programming for the Multi-Objective Urban Shipment ProblemEntropy10.3390/e2403038824:3(388)Online publication date: 9-Mar-2022
https://doi.org/10.3390/e24030388

Index Terms

Introduction to A Compromise Programming Based Method for Complex Scheduling and Planning Problems

Index terms have been assigned to the content through auto-classification.

Recommendations

A Genetic Algorithm for Multi-Objective Optimization in Complex Course Timetabling
ICSCA '21: Proceedings of the 2021 10th International Conference on Software and Computer Applications

The article discusses a multi-objective optimization approach for constructing an enrollment-based course timetable in universities from various sources. The model used the combination of mixed-integer and binary variables. It reaches the students' ...
Read More
Different Approaches of Evolutionary Algorithms to Multiple Objective RCPSP
ICBDC '22: Proceedings of the 7th International Conference on Big Data and Computing

Task assignments to the project members play a vital role in the project planning process. The project's quality, development time, and cost are criteria to indicate a success or failure project. These are affected by every single arrangement generated ...
Read More
Nadir compromise programming

In problem of portfolio selection, financial Decision Makers (DMs) explain objectives and investment purposes in the frame of multi-objective mathematic problems which are more consistent with decision making realities. At present, various methods have ...
Read More

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

IMMS '21: Proceedings of the 4th International Conference on Information Management and Management Science

August 2021

332 pages

ISBN:9781450384278

DOI:10.1145/3485190

Copyright © 2021 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 December 2021

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

IMMS 2021

IMMS 2021: 2021 4th International Conference on Information Management and Management Science

August 27 - 29, 2021

Chengdu, China

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
84
Total Downloads

Downloads (Last 12 months)41
Downloads (Last 6 weeks)15

Other Metrics

View Author Metrics

Citations

Cited By

Son NNguyet Ha TJAAFAR JAnh BGiang T(2023)Some Metaheuristics for Tourist Trip Design Problem2023 IEEE Symposium on Industrial Electronics & Applications (ISIEA)10.1109/ISIEA58478.2023.10212154(1-10)Online publication date: 15-Jul-2023
https://doi.org/10.1109/ISIEA58478.2023.10212154
Ngo SJaafar JIzzatdin ATong GBui A(2022)Some metaheuristic algorithms for solving multiple cross-functional team selection problemsPeerJ Computer Science10.7717/peerj-cs.10638(e1063)Online publication date: 9-Aug-2022
https://doi.org/10.7717/peerj-cs.1063
Ngo TJaafar JAziz IAftab MNguyen HBui N(2022)Metaheuristic Algorithms Based on Compromise Programming for the Multi-Objective Urban Shipment ProblemEntropy10.3390/e2403038824:3(388)Online publication date: 9-Mar-2022
https://doi.org/10.3390/e24030388

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Media

Figures

Other

Tables

View Table of Contents