Crowdsourcing software project scheduling based on group learning particle swarm optimization algorithm
To solve the three coupled subproblems of the crowdsourcing software project scheduling including devel-oper selection,task assignment and determination of the dedications,by introducing the reputation of the developers and considering the constraints such as task skills,working hours and team size,a mathematical model was con-structed aiming to maximize the completion quality and minimize the project duration simultaneously.A group learn-ing particle swarm optimization algorithm was proposed to solve the model,which adopted a three-segment hybrid encoding method and divided the population into three groups according to the fitness ranking.The number of parti-cles in different groups changed adaptively with the evolutionary generation,and each group employed distinct up-date strategies according to the differences of fitness values.The proposed algorithm was compared with 10 repre-sentative algorithms on 12 instances with different scales.Experimental results showed that the proposed algorithm could obtain a scheduling solution with higher precision.
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