A new approach for production project scheduling with time-cost-quality trade-off considering multi-mode resource-constraints under interval uncertainty

被引:10
|
作者
Ghasemi, M. [1 ]
Mousavi, S. M. [1 ]
Aramesh, S. [1 ]
Shahabi-Shahmiri, R. [2 ]
Zavadskas, E. K. [3 ]
Antucheviciene, J. [4 ]
机构
[1] Shahed Univ, Fac Engn, Dept Ind Engn, Tehran, Iran
[2] Univ Tehran, Coll Engn, Sch Ind Engn, Tehran, Iran
[3] Vilnius Gediminas Tech Univ, Inst Sustainable Construct, Vilnius, Lithuania
[4] Vilnius Gediminas Tech Univ, Fac Civil Engn, Dept Construct Management & Real Estate, Vilnius, Lithuania
关键词
Production scheduling; time-cost-quality trade-off; MRCPSP; bi-directional projection; interval data; pessimistic-optimistic approach; GROUP DECISION-MAKING; GENETIC ALGORITHM; TODIM METHOD; MODEL; STRATEGY; WEIGHTS; MAKERS;
D O I
10.1080/00207543.2022.2074322
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Due to today's competitive environment and information boom, companies are concerned about production planning in uncertain conditions. This paper integrates decision-making method with production scheduling model by considering limited resources. In this paper, a new mathematical model is extended for production project scheduling with multiple execution modes. The main aim of the formulation is to plan and schedule real production projects in uncertain environments. A new mixed-integer linear formulation is presented by considering trade-off of cost, time, as well as quality. Cost-time-quality trade-off is extended with the interval information. In the presented model, activity quality could be enhanced by reworking. The interval forms of some parameters, including duration, quality of activities, cost, and total available resources, are obtained by determining weights of experts and aggregating them. The presented group decision-making method is based on a bi-directional projection measure to deal with interval information. Since the mathematical model is multi-objective and some data are interval, a new modified solution method is developed for solving the model. The presented method for both decision-making and mathematical models is investigated by a real-world production project and two datasets to ascertain the accuracy of the model. Finally, an appropriate sensitivity analysis is proposed.
引用
收藏
页码:2962 / 2984
页数:23
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