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In the construction industry, contractors usually manage and execute multiple projects simultaneously. Typically, this situation involves sharing different types of resources, including cash, equipment, and manpower. The management of resources becomes a major challenge in these problems. In this situation, contractors are concerned with optimizing a number of different objectives which often conflict with one another. These objectives include duration, total cost, financing cost, required cash, profit, and resource fluctuations. This paper presents the development of a multiobjective scheduling optimization model for multiple construction projects using the fast elitist nondominated sorting genetic algorithm (NSGA-II). The purpose of the proposed model is to obtain optimal trade-offs between different projects’ objectives. The scheduling optimization model comprises submodels of project scheduling, resource allocation and leveling, and cash flow forecasting. The optimization model was successfully implemented and tested using different case studies of multiple projects of different sizes. The developed model is expected to help construction companies in solving the problems of prioritizing projects under resource-conflict conditions, allocating limited resources, and optimizing all the projects’ multiple objectives under certain funding limits.
El-Abbasy et al. (2017) studied this question.