Time-cost optimization in construction projects; Case study at al-Anbar hospital

Optimization of time and cost in construction projects has been subject to extensive research since the development of the Critical Path Method (CPM). Many researchers have investigated various versions of the well-known Time-Cost Trade-off (TCT) problem, including linear, convex, concave, and also the discrete (DCTC) version. Traditional methods, in the literature for optimizing time and cost of construction projects range from mathematical methods to evolutionary based ones, such genetic algorithms, particle swarm optimization, ant-colony optimization, and leap frog optimization. However, none of the existing research studies has dealt with the optimization of projects in which any small saving would be significant. Traditional approaches have all been applied to projects of less than 100 activities which are far less than what exists in real-world construction projects. The objective of this study is to utilize recent developments in computation technology and novel optimization techniques such as Constraint Programming (CP) to improve the current limitations in solving DTCT problems. This research investigated the complex nature of time and cost optimization in construction projects. The traditional optimization methods of solving TCT problems, such as mathematical programming and evolutionary-based methods were examined and their inefficiency in solving large TCT problems was verified. The major outcome of this study is that the initial experimentations using mathematical and evolutionary-based optimization methods demonstrated the need for a considerable amount of time for these methods to find a feasible solution before starting to improve them. Thus, the decision variables were initialized with the most crashed mode of construction for all the activities to ensure that the experimentations initialized with a feasible solution will reduce the required time of finding the initial feasible solution. KEYWORDS: Industrial Engineering, Project Time-Cost Problem, Critical Path Method, Optimization, Evolutionary Computation. March 2020, Page, 81 Science Code: 90