A hybrid of decomposition and domination based evolutionary algorithm for multi-objective software next release problem

In software industry, one common problem that the companies face is to decide what requirements should be implemented in the next release of the software. In a more realistic perspective, multiple objectives, such as cost and customer satisfaction, need to be considered when making the decision; thus the multi-objective formulations of the NRP become increasingly popular. This paper studies various multiobjective evolutionary algorithms(MOEAs) to address multi-objective NRP(MONRP). A novel multi-objective algorithm, MOEA/DD, is proposed to obtain trade-off solutions when deciding which requirements to be implemented in MONRP. The proposed MOEA/DD addresses several important issues of decomposition based MOEAs in context of MONRP by combining it with desirable feature of domination based MOEAs. A density based mechanism is proposed to switch between decomposition and domination archives when constructing the subpopulation of subproblems. Our experimental results suggest the proposed approach outperforms the state-of-art domination or decomposition based multi-objective MOEAs.