{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T18:03:13Z","timestamp":1774634593591,"version":"3.50.1"},"reference-count":70,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:00:00Z","timestamp":1755820800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Doctoral Research Startup Fund Project of Hubei Minzu University","award":["BS24035"],"award-info":[{"award-number":["BS24035"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>Complex task crowdsourcing (CTC) integrates distributed talent, knowledge, and ideas into innovation via the web; however, task decomposition remains a critical challenge. While existing studies focus primarily on workflow management for specific tasks, they leave a gap in decomposing more complex, creative tasks, which are characterized by the absence of objective ground truths, nonlinear dependencies, and non-sequential processes. To address this gap, we propose a novel integrated task decomposition framework for CTC that comprises three interconnected components. First, primary decomposition considers knowledge reuse by identifying similar past task decomposition schemes to inform the initial breakdown. Second, modifications to the scheme are guided by work breakdown structure (WBS)-based principles, which also serve as a foundation when no prior knowledge is available. Third, to enhance executability, a task package model is proposed to combine subtasks that share common resources, thereby reducing coordination costs and avoiding waste of workers\u2019 capabilities. To solve this model, we develop an improved non-dominated sorting genetic algorithm (NSGA-II) to generate the final decomposition scheme. A case study from ZBJ.COM validates the feasibility and effectiveness of the proposed framework. Experimental results demonstrate that, compared to baseline algorithms, the improved NSGA-II better balances conflicting objectives and generates non-dominated solution sets with higher diversity and more uniform distribution.<\/jats:p>","DOI":"10.3390\/systems13090728","type":"journal-article","created":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T12:31:26Z","timestamp":1755865886000},"page":"728","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["An Integrated Task Decomposition Framework Considering Knowledge Reuse and Resource Availability for Complex Task Crowdsourcing"],"prefix":"10.3390","volume":"13","author":[{"given":"Biyu","family":"Yang","sequence":"first","affiliation":[{"name":"Research Center for Ecological and Cultural Tourism of Western Hubei, Hubei Minzu University, Enshi City 445000, China"},{"name":"School of Economics and Management, Hubei Minzu University, Enshi City 445000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shixin","family":"Xie","sequence":"additional","affiliation":[{"name":"College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Longxiao","family":"Li","sequence":"additional","affiliation":[{"name":"School of Management, Chongqing University of Science and Technology, Chongqing 401331, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"111003","DOI":"10.1016\/j.engappai.2025.111003","article-title":"A gradient descent matrix factorization for microtask crowdsourcing","volume":"154","author":"Moayedikia","year":"2025","journal-title":"Eng. 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