This paper describes the software requirements prioritization task and provides a systematic approach to\ndetermine what needs to be included in the next release of a software product. Minimizing the total cost\nof adding a new feature in the next release and maximizing overall customer satisfaction are contradictory\nobjectives. In this paper, first, an adaptive multi-objective prioritization model is discussed. Then we\ndescribe how discrete inverse problems ideas can in fact be formulated to obtain a smooth local ââ?¬Å?Added\nDegree of Importanceââ?¬Â (ADI) function of client requirements which could be used to classify and\nprioritize the software requirements for next release. The numerical implementation of the proposed\nmodel with a case study on software requirements selection shows the effectiveness of the multi-objective\ninverse model (IM) approach. The proposed model have been compared with some of the recent relevant\nmodels. Main future of the model is that it has been designed by the assignment of a real score for each of\nthe requirements unlike just classification provided in the literature.
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