An Evolutionary Computation Method of Crowdsourcing Ideation that Integrates the Balanced-exploration Pattern

doi:10.3901/JME.2017.15.073

Abstract

Abstract: Crowdsourcing ideation recruits crowds to complete design tasks such as product design and graphic design, acting as an important method of generating design solutions. However, crowdsourcing participants are amateurs and hard to organize. An evolutionary computation method of crowdsourcing ideation that integrates the balanced-exploration pattern is proposed in order to combine experts' competence with computers' computing capacity. This method holds the process of crowdsourcing ideation based on the study of design experts' behavior so that the crowds act as design experts, thus enhancing the quality of design solutions. Specifically, the balanced-exploration pattern summarized from the experts' behavior, including "constant information seeking", "structural exploration", "mix of breadth-first and depth-first modes of solution development", and "mix of solution-exploration and solution-review" is incorporated, the evolutionary fitness of design solutions is calculated, the coding, crossover, and mutation operations are refined, thus orienting the evolution of design solutions. To verify this method, an experiment of crowdsourcing ideation has been conducted during which 252 participants produces three generation of design solutions. This case validates that the crowdsourcing ideation method increases the diversity of design solutions and improves the quality of design ideas.

Key words: behavior pattern, crowdsourcing ideation, design cognition, evolutionary computation

CLC Number:

TB472

XIANG Wei, SUN Lingyun, XIA Suochen, XU Jiang. An Evolutionary Computation Method of Crowdsourcing Ideation that Integrates the Balanced-exploration Pattern[J]. Journal of Mechanical Engineering, 2017, 53(15): 73-80.

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