Solving “Resource Constrained Project Scheduling Problem” (RCPSP) with Bench Marked Hybrid Algorithm’s

In the paper, we give illustrated reviews, new approaches and results of how rcps –problems are being solved with Hybrid algorithm’s. Firstly, considering Hybrid Genetic Algorithm (HGA), Vicente a et al 2007, introducing many changes in Genetic algorithm (GA) paradigm, resulting in HGA giving fast and high quality algorithms out performing state-of-the-art-algorithm (SOTAA). for rcps-problem. Secondly, Lin a et al 2005 claims a Hybrid Meta-heuristic ANGEL for rcpsproblem. ANGEL combines ant colony optimization (ACO), GA and Local search strategy. For ANGEL to proceed it firstly searches for solution space and generates activity lists for the initial population from ACO. With GA following execution and pheromone is updated in ACO. Proposing an efficient local search method when ACO and GA reaching optimum solutions. Thirdly, Sonda Elloumi a et al 2009 implementing multi-mode rcps-problem with Hybrid rank based evolutionary algorithm (EA) , proposing i)transforming single objective multi-mode rcpsproblem to bi-objective to cope with potential violation to non-renewable resource constraints and relaxing latter constraints, ii) fitness function on an adaptive relying clustering method. Lastly, Ling Wang et al 2012 presents Hybrid estimation distribution algorithm (HEDA), here individuals encode based on extended activity list (EAL) and then decoding with serial generation scheme (SGS).