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This paper presents a Quantum-inspired Multi-objective Differential Evolution Algorithm (QMDEA) for the selection of software requirements, an issue in Requirements engineering phase of software development life cycle. Generally the software development process is iterative or incremental in nature, as request for new requirements keep coming from the customers from time to time for inclusion in the next release of the software. Due to the feasibility reasons it is not possible for a company to incorporate all the requirements in the software product. Consequently, it becomes a challenging task for the company to select a subset of the requirements to be included, by keeping the business goals in view. The problem is to identify a set of requirements to be included in the next release of the product, by minimizing the cost and maximizing the customer satisfaction. As minimizing the cost and maximizing the customer satisfaction are contradictory objectives, the problem is multi-objective and is also NP-hard in nature. Therefore it cannot be solved efficiently using traditional optimization techniques especially for the large problem instances. QMDEA combines the preeminent features of Differential Evolution and Quantum Computing. The features of QMDEA help in achieving quality Pareto-optimal front solutions with faster convergence. The performance of QMDEA is tested on six benchmark problems derived from the literature. The comparison of the obtained results indicates superior performance over the other methods reported in the literature.