Multi-Objective Multi-Project Construction Scheduling Optimization
In construction industry, contractors usually manage and execute multiple projects simultaneously within their portfolio. This involves sharing of limited resources such as funds, equipment, manpower, and others among different projects, which increases the complexity of the scheduling process. The allocation of scarce resources then becomes a major objective of the problem and several compromises should be made to solve the problem to the desired level of optimality. In such cases, contractors are generally concerned with optimizing a number of different objectives, often conflicting among each other. Thus, the main objective of this research is to develop a multi-objective scheduling optimization model for multiple construction projects considering both financial and resource aspects under a single platform. The model aims to help contractors in devising schedules that obtain optimal/near optimal tradeoffs between different projects’ objectives, namely: duration of multiple projects, total cost, financing cost, maximum required credit, profit, and resource fluctuations. Moreover, the model offers the flexibility in selecting the desired set of objectives to be optimized together. Three management models are built in order to achieve the main objective which involves the development of: (1) a scheduling model that establishes optimal/near optimal schedules for construction projects; (2) a resource model to calculate the resource fluctuations and maximum daily resource demand; and (3) a cash flow model to calculate projects’ financial parameters. The three management models are linked with the designed optimization model, which consequently performs operations of the elitist non-dominated sorting genetic algorithm (NSGA-II) technique, in three main phases: (1) population initialization; (2) fitness evaluation; and (3) generation evolution. The optimization model is implemented and tested using different case studies of different project sizes obtained from literature. Finally, an automated tool using C# language is built with a friendly graphical user interface to facilitate solving multi-objective scheduling optimization problems for contractors and practitioners.