EFFECTIVENESS OF MULTI-OBJECTIVE GENETIC ALGORITHM OPTIMIZATION IN CONSTRUCTION INDUSTRY

In our field, the limited time needed to achieve a specific project needs adjustment with the cost and that's one of the biggest problems in construction industry. This is known as time–cost trade-off (TCT) problem. Several optimization strategies were proposed over the years for each objective at a time. And this affects adversely the other objectives that haven't been optimized. Then multi-objective optimization solutions began to develop. One of them was using the genetic algorithm to reach the optimum solution in various construction projects. In this paper we introduce a simple method that collect the characteristics of the project, direct costs (labor, material, equipment and subcontractors), indirect costs and with using multi elitism genetic algorithms techniques, that have a great impact on improving time-cost trade-off problem, that deals with all the costs of the project. Finally, the optimal balance of time and total cost is reached. Which provide the optimal selection of construction methods for project activities.