{'fraction_non_alphanumeric': 0.012782694198623401, 'fraction_numerical': 0.0019665683382497543, 'mean_word_length': 6.020689655172414, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Multiobjective evolutionary algorithm for software project portfolio optimization

Large software companies have to plan their project portfolio to maximize potential portfolio return and strategic alignment, while balancing various preferences, and considering limited resources. However, software project portfolios are challenging to describe for optimization in a practical way that allows efficient optimization. In this paper we propose an approach to describe software project portfolios with a set of multiobjective criteria for portfolio managers using the COCOMO II model and introduce a multiobjective evolutionary approach, mPOEMS, to find the Pareto-optimal front efficiently. The proposed approach was evaluated on a set of 50 projects that follow the validated COCOMO II model criteria. Major results are: the proposed project portfolio management approach was found usable and useful; the mPOEMS algorithm shows capabilities for efficiently solving the combinatorial optimization problem of this type.