A multiheuristic approach to resource constrained project scheduling: An adaptive hybrid genetic algorithm

The resource constrained project scheduling problem (RCPSP) is one of the most challenging problems and of great practical importance because its general model can be used for application in product development, production planning, and a wide variety of scheduling applications. Although various solution approaches to the RCPSP have been proposed for over four decades, most procedures do not have a capability to find optimal solutions for project networks with 60 activities or more and the use of a hybrid approach, which combines global search with local search to the RCPSP, has not been yet accomplished. The development of an Adaptive Hybrid Genetic Algorithm-based Search Simulator (AHGASS) was motivated by both the lack of success in finding an efficient optimal solution algorithm and the need for a hybrid global-local search approach to the problem.; This research proposes a new adaptive hybrid genetic algorithm that solves the RCPSP more effectively and efficiently by using the simple genetic algorithm (SGA) and the random walk algorithm (RWA). A new hybrid strategy to combine the SGA for global search with the RWA for local search was identified through the review of literature. Based on the strategy, a computer program, AHGASS, was developed using JAVA language to enable users to solve a variety of problems given the users' input. AHGASS was validated with the comparison of the existing methods using numerous standard problem instance sets available in the literature and also implemented with two case studies of construction projects for the feasibility of the algorithm.; The results of the validation showed that AHGASS produces an accurate and consistent solution to the RCPSP, improves performance over SGA, produces a competitive solution over the existing algorithms, is capable of solving a large-sized problem, and thus can be an algorithm general enough for the RCPSP. Major contributions of this research are that AHGASS is the first approach to the RCPSP in contrast to the approaches of the existing hybrid methods and that it can be a promising alternative to the RCPSP as it combines the best aspects of a global optimization approach with a local approach.