Two-list genetic algorithm for optimizing work package schemes to minimize project costs

Abstract

Optimizing work package schemes is challenging under uncertain task duration. This paper develops a two-list genetic algorithm (TLGA) to optimize work package schemes with minimal project costs under deterministic and stochastic task durations. First, this paper defines the deterministic and stochastic work package scheme problem. Second, the TLGA, comprising a task and a work packaging list, is developed to generate the deterministic work package scheme and issue work package policies through stochastic distribution simulations. Moreover, a graphical user interface with TLGA is developed to enhance its practical application. Finally, experiments show that the TLGA can reduce the total cost by up to 19.57% in the deterministic problem, and the minimum gap between the TLGA and the state-of-the-art heuristics is only 3.91%. However, the TLGA can reduce the running time by about 66%. In the stochastic problem, this paper analyzes the impact of stochastic distributions on work package policies.