Solution for the Nonlinear Multi-Objective Model in Construction Projects Using Improved Particle Swarm Optimization

In project management, spending minimum time and cost while achieving maximum quality is of great significance to its success. Consequently, it is vital to find an optimal equilibrium between the three objectives of construction projects. To achieve this goal, this study presents an advanced nonlinear multiobjective model to solve the time-cost-quality trade-off problem. We assume that the quality of an activity is influenced by its duration and cost and quantify the quality of a project by calculating the mean of the quality coefficients of all the activities. The concepts of value management are introduced to formulate the evaluation function, so that the solutions are further optimized for project managers’ decision making. When solving the model, an improved Particle Swarm Optimization (PSO) is developed by introducing genetic operators and immune selection to the original PSO for higher efficiency and faster convergence. The efficiency and reliability of the proposed algorithm in generating optimal solutions for the trade-off problems are demonstrated through an application example.