eprintid: 15656
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/56/56
datestamp: 2023-11-10 03:30:17
lastmod: 2023-11-10 03:30:17
status_changed: 2023-11-10 02:00:02
type: article
metadata_visibility: show
creators_name: Son, N.T.
creators_name: Jaafar, J.
creators_name: Aziz, I.A.
creators_name: Anh, B.N.
creators_name: Binh, H.D.
creators_name: Aftab, M.U.
title: A Compromise Programming to Task Assignment Problem in Software Development Project
ispublished: pub
keywords: Decision making; Genetic algorithms; Multiobjective optimization; Scheduling; Software design, Assignment problems; Bidding process; Compromise programming; Makespan; Mop; Project quality; Rcpsp; Scheduling process; Software development projects; Tasks assignments, Combinatorial optimization
note: cited By 6
abstract: The scheduling process that aims to assign tasks tomembers is a difficult job in project management. It plays a prerequisite role in determining the project's quality and sometimes winning the bidding process. This study aims to propose an approach based on multi-objective combinatorial optimization to do this automatically. The generated schedule directs the project to be completed with the shortest critical path, at the minimum cost, while maintaining its quality. There are several real-world business constraints related to human resources, the similarity of the tasks added to the optimizationmodel, and the literature's traditional rules. To support the decision-maker to evaluate different decision strategies, we use compromise programming to transform multiobjective optimization (MOP) into a single-objective problem. We designed a genetic algorithm scheme to solve the transformed problem. The proposed method allows the incorporation of the model as a navigator for search agents in the optimal solution search process by transferring the objective function to the agents' fitness function. The optimizer can effectively find compromise solutions even if the user may or may not assign a priority to particular objectives. These are achieved through a combination of nonpreference and preference approaches. The experimental results show that the proposed method worked well on the tested dataset. © 2021 Tech Science Press. All rights reserved.
date: 2021
publisher: Tech Science Press
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115907263&doi=10.32604%2fcmc.2021.017710&partnerID=40&md5=84b4f2613dd4ced30fc18142c37cb7f0
id_number: 10.32604/cmc.2021.017710
full_text_status: none
publication: Computers, Materials and Continua
volume: 69
number: 3
pagerange: 3429-3444
refereed: TRUE
issn: 15462218
citation:   Son, N.T. and Jaafar, J. and Aziz, I.A. and Anh, B.N. and Binh, H.D. and Aftab, M.U.  (2021) A Compromise Programming to Task Assignment Problem in Software Development Project.  Computers, Materials and Continua, 69 (3).  pp. 3429-3444.  ISSN 15462218