Multi-objective Hyper-heuristic Evolutionary Algorithm

This paper presents a Multi-objective Hyper-heuristic Evolutionary Algorithm (MHypEA) for the solution of Scheduling and Inspection Planning in Software Development Projects. Scheduling and Inspection planning is a vital problem in software engineering whose main objective is to schedule the persons to various activities in the software development process such as coding, inspection, testing and rework in such a way that the quality of the software product is maximum and at the same time the project make span and cost of the project are minimum. The problem becomes challenging when the size of the project is huge. The MHypEA is an effective metaheuristic search technique for suggesting scheduling and inspection planning. It incorporates twelve low-level heuristics which are based on different methods of selection, crossover and mutation operations of Evolutionary Algorithms. The selection mechanism to select a lowlevel heuristic is based on reinforcement learning with adaptive weights. The efficacy of the algorithm has been studied on randomly generated test problem.