{"title":"Finding Pareto Optimal Front for the Multi- Mode Time, Cost Quality Trade-off in Project Scheduling","authors":"H. Iranmanesh, M. Skandari, M. Allahverdiloo","doi":"10.5281/ZENODO.1074392","DOIUrl":null,"url":null,"abstract":"Project managers are the ultimate responsible for the\noverall characteristics of a project, i.e. they should deliver the project\non time with minimum cost and with maximum quality. It is vital for\nany manager to decide a trade-off between these conflicting\nobjectives and they will be benefited of any scientific decision\nsupport tool. Our work will try to determine optimal solutions (rather\nthan a single optimal solution) from which the project manager will\nselect his desirable choice to run the project. In this paper, the\nproblem in project scheduling notated as\n(1,T|cpm,disc,mu|curve:quality,time,cost) will be studied. The\nproblem is multi-objective and the purpose is finding the Pareto\noptimal front of time, cost and quality of a project\n(curve:quality,time,cost), whose activities belong to a start to finish\nactivity relationship network (cpm) and they can be done in different\npossible modes (mu) which are non-continuous or discrete (disc), and\neach mode has a different cost, time and quality . The project is\nconstrained to a non-renewable resource i.e. money (1,T). Because\nthe problem is NP-Hard, to solve the problem, a meta-heuristic is\ndeveloped based on a version of genetic algorithm specially adapted\nto solve multi-objective problems namely FastPGA. A sample project\nwith 30 activities is generated and then solved by the proposed\nmethod.","PeriodicalId":224473,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"50","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"World Academy of Science, Engineering and Technology, International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5281/ZENODO.1074392","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 50
Abstract
Project managers are the ultimate responsible for the
overall characteristics of a project, i.e. they should deliver the project
on time with minimum cost and with maximum quality. It is vital for
any manager to decide a trade-off between these conflicting
objectives and they will be benefited of any scientific decision
support tool. Our work will try to determine optimal solutions (rather
than a single optimal solution) from which the project manager will
select his desirable choice to run the project. In this paper, the
problem in project scheduling notated as
(1,T|cpm,disc,mu|curve:quality,time,cost) will be studied. The
problem is multi-objective and the purpose is finding the Pareto
optimal front of time, cost and quality of a project
(curve:quality,time,cost), whose activities belong to a start to finish
activity relationship network (cpm) and they can be done in different
possible modes (mu) which are non-continuous or discrete (disc), and
each mode has a different cost, time and quality . The project is
constrained to a non-renewable resource i.e. money (1,T). Because
the problem is NP-Hard, to solve the problem, a meta-heuristic is
developed based on a version of genetic algorithm specially adapted
to solve multi-objective problems namely FastPGA. A sample project
with 30 activities is generated and then solved by the proposed
method.