{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T20:51:23Z","timestamp":1761598283989,"version":"build-2065373602"},"reference-count":50,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2020,12,13]],"date-time":"2020-12-13T00:00:00Z","timestamp":1607817600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["418727532"],"award-info":[{"award-number":["418727532"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Project Planning and Control (PPC) problems with stochastic job processing times belong to the problem class of Stochastic Resource-Constrained Multi-Project Scheduling Problems (SRCMPSP). A practical example of this problem class is the industrial domain of customer-specific assembly of complex products. PPC approaches have to compensate stochastic influences and achieve high objective fulfillment. This paper presents an efficient simulation-based optimization approach to generate Combined Priority Rules (CPRs) for determining the next job in short-term production control. The objective is to minimize project-specific objectives such as average and standard deviation of project delay or makespan. For this, we generate project-specific CPRs and evaluate the results with the Pareto dominance concept. However, generating CPRs considering stochastic influences is computationally intensive. To tackle this problem, we developed a 2-phase algorithm by first learning the algorithm with deterministic data and by generating promising starting solutions for the more computationally intensive stochastic phase. Since a good deterministic solution does not always lead to a good stochastic solution, we introduced the parameter Initial Copy Rate (ICR) to generate an initial population of copied and randomized individuals. Evaluating this approach, we conducted various computer-based experiments. Compared to Standard Priority Rules (SPRs) used in practice, the approach shows a higher objective fulfilment. The 2-phase algorithm can reduce the computation effort and increases the efficiency of generating CPRs.<\/jats:p>","DOI":"10.3390\/a13120337","type":"journal-article","created":{"date-parts":[[2020,12,13]],"date-time":"2020-12-13T20:56:57Z","timestamp":1607893017000},"page":"337","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["An Algorithm for Efficient Generation of Customized Priority Rules for Production Control in Project Manufacturing with Stochastic Job Processing Times"],"prefix":"10.3390","volume":"13","author":[{"given":"Mathias","family":"K\u00fchn","sequence":"first","affiliation":[{"name":"Institute of Material Handling and Industrial Engineering, Technische Universit\u00e4t Dresden, 01062 Dresden, Germany"}]},{"given":"Michael","family":"V\u00f6lker","sequence":"additional","affiliation":[{"name":"Institute of Material Handling and Industrial Engineering, Technische Universit\u00e4t Dresden, 01062 Dresden, Germany"}]},{"given":"Thorsten","family":"Schmidt","sequence":"additional","affiliation":[{"name":"Institute of Material Handling and Industrial Engineering, Technische Universit\u00e4t Dresden, 01062 Dresden, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,13]]},"reference":[{"key":"ref_1","unstructured":"Bischoff, J., Taphorn, C., Wolter, D., Braun, N., Fellbaum, M., Goloverov, A., Ludwig, S., Hegmanns, T., Prasse, C., and Henke, M. 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