Improving Dijkstra’s algorithm for Estimating Project Characteristics and Critical Path

Abstract

Developing a project planning structure for all industries is a technological challenge involving evaluating several restrictions for each activity’s respective task and its planning tools. Any restriction affects the completion time, operating costs, and overall project performance. Programme Evaluation Review Technique (PERT) and Critical Path Method (CPM) processes made many researchers study the possible ways of finding the critical paths and activities in the network. The advancement of the CPM and PERT towards a probabilistic environment is still a long way off. However, Artificial intelligence approaches such as the Genetic Algorithm, Dijkstra’s algorithm, and others are utilized for network analysis within the project management framework. This study is to help the project manager plan schedule for a construction project to determine the expected completion time. In this research paper, we describe a method for obtaining the earliest and latest times of a critical path using modified Dijkstra’s algorithm with triangular fuzzy numbers. Forward pass and backward pass algorithms are designed to find the optimal path for the proposed method. Numerical examples are also illustrated for the same. Simulation results are included by the use of the “C” program. Finally, a comparison is made with the traditional method PERT.