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...

Full description

Saved in:
Bibliographic Details
Main Authors: Hongwei Li, Yuvraj Gajpal, Chirag Surti, Dongliang Cai, Amit Kumar Bhardwaj
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