{"title":"Two Scenario-Based Heuristics for Stochastic Shift Design Problem with Task-Based Demand","authors":"Zhiying Wu, Qing-xin Chen, Ning Mao, Guoning Xu","doi":"10.3390/app131810070","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a deterministic shift design model with task-based demand and give the corresponding stochastic version with a probability constraint such that the shift plan designed is staffed with the workforce with a certain probability of performing all given tasks. Since we currently find no suitable methods for solving this stochastic model from the literature related to solving stochastic shift design models, we developed a single-stage heuristic method based on statistics, whose main idea is to reduce the occurrence of manpower shortage by prolonging the resource occupation time of a task, but this leads to a serious waste of resources, which is common in solving resource allocation problems with uncertain durations. To reduce the cost of wastage, we also propose a two-stage heuristic approach that is a two-stage heuristic with an evolutionary strategy. The two heuristics show their effectiveness in solving the proposed stochastic model in numerical experiments, and the two-stage heuristic significantly outperforms the one-stage heuristic in cost optimization and solution time stability.","PeriodicalId":48760,"journal":{"name":"Applied Sciences-Basel","volume":" ","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Sciences-Basel","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.3390/app131810070","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we propose a deterministic shift design model with task-based demand and give the corresponding stochastic version with a probability constraint such that the shift plan designed is staffed with the workforce with a certain probability of performing all given tasks. Since we currently find no suitable methods for solving this stochastic model from the literature related to solving stochastic shift design models, we developed a single-stage heuristic method based on statistics, whose main idea is to reduce the occurrence of manpower shortage by prolonging the resource occupation time of a task, but this leads to a serious waste of resources, which is common in solving resource allocation problems with uncertain durations. To reduce the cost of wastage, we also propose a two-stage heuristic approach that is a two-stage heuristic with an evolutionary strategy. The two heuristics show their effectiveness in solving the proposed stochastic model in numerical experiments, and the two-stage heuristic significantly outperforms the one-stage heuristic in cost optimization and solution time stability.
期刊介绍:
Applied Sciences (ISSN 2076-3417) provides an advanced forum on all aspects of applied natural sciences. It publishes reviews, research papers and communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. Electronic files and software regarding the full details of the calculation or experimental procedure, if unable to be published in a normal way, can be deposited as supplementary electronic material.