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

Seyed Meysam Mousavi | M. Ghasemi | S. Aramesh | R. Shahabi-Shahmiri | E.K. Zavadskas | J.Antucheviciene

---

URL :   http://research.shahed.ac.ir/WSR/WebPages/Report/PaperView.aspx?PaperID=169789
Date :  2022/09/07
Publish in :    International Journal of Production Research

Link :  https://www.tandfonline.com/doi/abs/10.1080/00207543.2022.2074322?cookieSet=1
Keywords :production scheduling, time-cost-quality trade-off, MRCPSP, bi-directional projection, interval data, Pessimistic-optimistic approach

Abstract :

---

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, activities 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. Computational results show that the presented mathematical model and interval solution approach has been efficiently tuned to find high-quality solutions.