Closure to “Ant Colony Optimization for Multimode Resource-Constrained Project Scheduling” by Hong Zhang

Abstract

Many thanks for the comments of the discussers regarding the paper. The discussers primarily remarked that the examples used for comparison among the methods of ant colony optimization (ACO), genetic algorithm (GA), and particle swarm optimization (PSO) are very small because the metaheuristic methods are inefficient (e.g., time consuming) when handling large-scale problems. The discussers also suggested that future work focus on introducing efficient methods to handle practical sized problems. The discussers finally concluded that introducing new metaheuristics to achieve minor performance improvement to small textbook-type problems has no practical value. In consideration of the comments of the discussers, some points are provided in the following. 1. The paper focused on introducing an alternative metaheuristic method, i.e., an ACOmethod, for solving multimode resourceconstrained project scheduling problems in comparison with the GA and PSO methods. Although the examples used for comparison are not large, the performances of the methods under comparison are meaningful because they are compared under the same conditions, such as the same computer platform. 2. It is difficult and time consuming for the ACO method to handle practical sized problems, so the ACO method needs to be developed further with regard to computing efficiency by developing new computing techniques, such as the parallel computing framework described by Kandil and El-Rayes (2005) or other alternative computing frameworks, in consideration of the inconvenience or unavailability of multiple processors for general users. 3. The number of activities in a project may differ according to various levels of decomposing and different management focuses or periods for different contractors, so small or medium sized projects also represent practical problems. Meanwhile, when considering multiple modes of activities and resource constraints, optimal scheduling of these small or medium size projects is also complicated, in contrast to the large sized projects that do not consider multiple modes of activities and resource constraints. The discussers’ comments are meaningful and constructive for further studies into ACO and other metaheuristic methods for solving project scheduling problems of practical sizes.