Nature-Inspired Metaheuristics for Two-Agent Scheduling with Due Date and Release Time
This paper delves into a two-agent scheduling problem in which two agents are competing for a single resource. Each agent has a set of jobs to be processed by a single machine. The processing time, release time, weight, and the due dates of each job are known in advance. Both agents have their objec...
Saved in:
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2020-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2020/1385049 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
_version_ | 1832550860741148672 |
---|---|
author | Hongwei Li Yuvraj Gajpal Chirag Surti Dongliang Cai Amit Kumar Bhardwaj |
author_facet | Hongwei Li Yuvraj Gajpal Chirag Surti Dongliang Cai Amit Kumar Bhardwaj |
author_sort | Hongwei Li |
collection | DOAJ |
description | This paper delves into a two-agent scheduling problem in which two agents are competing for a single resource. Each agent has a set of jobs to be processed by a single machine. The processing time, release time, weight, and the due dates of each job are known in advance. Both agents have their objectives, which are conflicting in nature. The first agent tries to minimize the total completion time, while the second agent tries to minimize the number of tardy jobs. The two agents’ scheduling problem, an NP-hard problem, has a wide variety of applications ranging from the manufacturing industry to the cloud computing service provider. Due to the wide applicability, each variation of the problem requires a different algorithm, adapted according to the user’s requirements. This paper provides mathematical models, heuristic algorithms, and two nature-based metaheuristic algorithms to solve the problem. The algorithm’s performance was gauged against the optimal solution obtained from the AMPL-CPLEX solver for both solution quality and computational time. The outlined metaheuristics produce a solution that is comparable with a short computational time. The proposed metaheuristics even have a better solution than the CPLEX solver for medium-size problems, whereas the computation times are much less than the CPLEX solvers. |
format | Article |
id | doaj-art-bf8d86a954104776a51acb0e653871d5 |
institution | Kabale University |
issn | 1076-2787 1099-0526 |
language | English |
publishDate | 2020-01-01 |
publisher | Wiley |
record_format | Article |
series | Complexity |
spelling | doaj-art-bf8d86a954104776a51acb0e653871d52025-02-03T06:05:40ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/13850491385049Nature-Inspired Metaheuristics for Two-Agent Scheduling with Due Date and Release TimeHongwei Li0Yuvraj Gajpal1Chirag Surti2Dongliang Cai3Amit Kumar Bhardwaj4Department of Supply Chain Management, I.H. Asper School of Business, University of Manitoba, Winnipeg R3T 5V4, Manitoba, CanadaDepartment of Supply Chain Management, I.H. Asper School of Business, University of Manitoba, Winnipeg R3T 5V4, Manitoba, CanadaDepartment of Information System, Analytics and Supply Chain Management College of Business, Rider University, 2 083 Lawrenceville Rd, Lawrenceville 08648, NJ, USASchool of Finance, Southwestern University of Finance and Economics, Chengdu 610000, Sichuan, ChinaL.M. Thapar School of Management, Thapar Institute of Engineering & Technology, Dera Bassi Campus, Patiala, Punjab, IndiaThis paper delves into a two-agent scheduling problem in which two agents are competing for a single resource. Each agent has a set of jobs to be processed by a single machine. The processing time, release time, weight, and the due dates of each job are known in advance. Both agents have their objectives, which are conflicting in nature. The first agent tries to minimize the total completion time, while the second agent tries to minimize the number of tardy jobs. The two agents’ scheduling problem, an NP-hard problem, has a wide variety of applications ranging from the manufacturing industry to the cloud computing service provider. Due to the wide applicability, each variation of the problem requires a different algorithm, adapted according to the user’s requirements. This paper provides mathematical models, heuristic algorithms, and two nature-based metaheuristic algorithms to solve the problem. The algorithm’s performance was gauged against the optimal solution obtained from the AMPL-CPLEX solver for both solution quality and computational time. The outlined metaheuristics produce a solution that is comparable with a short computational time. The proposed metaheuristics even have a better solution than the CPLEX solver for medium-size problems, whereas the computation times are much less than the CPLEX solvers.http://dx.doi.org/10.1155/2020/1385049 |
spellingShingle | Hongwei Li Yuvraj Gajpal Chirag Surti Dongliang Cai Amit Kumar Bhardwaj Nature-Inspired Metaheuristics for Two-Agent Scheduling with Due Date and Release Time Complexity |
title | Nature-Inspired Metaheuristics for Two-Agent Scheduling with Due Date and Release Time |
title_full | Nature-Inspired Metaheuristics for Two-Agent Scheduling with Due Date and Release Time |
title_fullStr | Nature-Inspired Metaheuristics for Two-Agent Scheduling with Due Date and Release Time |
title_full_unstemmed | Nature-Inspired Metaheuristics for Two-Agent Scheduling with Due Date and Release Time |
title_short | Nature-Inspired Metaheuristics for Two-Agent Scheduling with Due Date and Release Time |
title_sort | nature inspired metaheuristics for two agent scheduling with due date and release time |
url | http://dx.doi.org/10.1155/2020/1385049 |
work_keys_str_mv | AT hongweili natureinspiredmetaheuristicsfortwoagentschedulingwithduedateandreleasetime AT yuvrajgajpal natureinspiredmetaheuristicsfortwoagentschedulingwithduedateandreleasetime AT chiragsurti natureinspiredmetaheuristicsfortwoagentschedulingwithduedateandreleasetime AT dongliangcai natureinspiredmetaheuristicsfortwoagentschedulingwithduedateandreleasetime AT amitkumarbhardwaj natureinspiredmetaheuristicsfortwoagentschedulingwithduedateandreleasetime |