An Advanced Stochastic Time-Cost Tradeoff Analysis Based on a CPM-Guided Genetic Algorithm

摘要

This article presents an advanced stochastic time-cost tradeoff (ASTCT) method that performs time-cost tradeoff analysis by identifying optimal set(s) of construction methods for activities, hence reducing the project completion time and cost simultaneously. ASTCT involves a stochastic time-cost tradeoff analysis method based on a critical path method (CPM)-guided genetic algorithm (GA). It makes use of CPM schedule data exported from a project management software, and alternative construction methods obtained from estimators (i.e., normal and accelerated durations and costs) for each activity. It simulates schedule networks, identifies an optimal set of GA parameters (i.e., population size, crossover rate, mutation rate, and stopping rule), implements several GA cycles, and computes near-optimal solution(s) exhaustively. This study is of value to practitioners because ASTCT improves the computation time, reliability, and usability of existing GA-based time-cost tradeoff methods. The study is also of relevance to researchers because it facilitates experiments using different GA parameters expeditiously. Two test cases verify the usability and validity of the computational methods.