Population dynamics modeling of crowdsourcing as an evolutionary Cooperation-Competition game for fulfillment capacity balancing and optimization of smart manufacturing services

IF 6.7 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
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引用次数: 0

Abstract

Crowdsourcing has become an integral part of various industrial systems, with evolutionary dynamics playing a crucial role in group interactions within structured populations. This paper explores the significance of understanding population dynamics in crowdsourcing, particularly in the context of manufacturer crowds delivering manufacturing services. To ensure the platform’s prosperity, it is essential to address the key challenge of matching and balancing different manufacturers’ fulfillment capacities.

To tackle this challenge, we present a population dynamics model and a Moran process formulation based on evolutionary cooperation-competition game theory. These tools offer valuable insights into the growth rate of specific user types participating in crowdsourcing activities. Moreover, we have devised an optimization strategy that utilizes the population dynamics model and Moran process simulations to effectively stimulate user growth.

To demonstrate the efficacy of our approach, we focus on the application of tank trailer crowdsourced manufacturing. Through a comprehensive testing case study, we showcase how our proposed model can effectively motivate and balance manufacturers’ participation levels in a tournament-based bidding process for crowdsourcing.

众包已成为各种工业系统不可或缺的一部分,而进化动力学在结构化群体的群体互动中发挥着至关重要的作用。本文探讨了理解众包中群体动力学的意义,尤其是在制造商众包提供制造服务的背景下。为了确保平台的繁荣,必须解决匹配和平衡不同制造商的履约能力这一关键挑战。为了应对这一挑战,我们提出了基于进化合作-竞争博弈理论的种群动力学模型和莫兰过程公式。这些工具为了解参与众包活动的特定用户类型的增长率提供了宝贵的见解。此外,我们还设计了一种优化策略,利用种群动力学模型和莫兰过程模拟来有效刺激用户增长。为了证明我们的方法的有效性,我们将重点放在坦克拖车众包制造的应用上。通过综合测试案例研究,我们展示了我们提出的模型如何在基于锦标赛的众包竞标过程中有效激励和平衡制造商的参与水平。
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来源期刊
Computers & Industrial Engineering
Computers & Industrial Engineering 工程技术-工程:工业
CiteScore
12.70
自引率
12.70%
发文量
794
审稿时长
10.6 months
期刊介绍: Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.
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