FengLian Yuan , Bo Huang , JianYong Lv , MeiJi Cui
{"title":"利用广义 Petri 网和高度知情的启发式搜索安排 AMS","authors":"FengLian Yuan , Bo Huang , JianYong Lv , MeiJi Cui","doi":"10.1016/j.cor.2024.106912","DOIUrl":null,"url":null,"abstract":"<div><div>The design of the heuristic function in a Petri-net(PN)-based A<span><math><msup><mrow></mrow><mrow><mo>∗</mo></mrow></msup></math></span> search significantly impacts search efficiency and schedule quality for automated manufacturing systems (AMSs). In Luo et al. (2015), two admissible heuristic functions were formulated for an A<span><math><msup><mrow></mrow><mrow><mo>∗</mo></mrow></msup></math></span> search based on place-timed PNs to schedule AMSs. To broaden its application scenarios and enhance search efficiency, this paper proposes a new heuristic function whose calculations take account of multiple resource acquisitions, weighted arcs, redundant resource units, and outdated resources, which are commonly encountered in practical AMSs but usually not considered. The proposed one can deal with generalized PNs, offering broader application scenarios than ordinary PNs. In addition, it is proven to be admissible and more informed than its counterparts, ensuring that the obtained schedules are optimal and making the timed PN-based A<span><math><msup><mrow></mrow><mrow><mo>∗</mo></mrow></msup></math></span> search more efficient. To validate the efficacy and efficiency of the proposed method, several benchmark systems are tested.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"175 ","pages":"Article 106912"},"PeriodicalIF":4.1000,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Scheduling AMSs with generalized Petri nets and highly informed heuristic search\",\"authors\":\"FengLian Yuan , Bo Huang , JianYong Lv , MeiJi Cui\",\"doi\":\"10.1016/j.cor.2024.106912\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The design of the heuristic function in a Petri-net(PN)-based A<span><math><msup><mrow></mrow><mrow><mo>∗</mo></mrow></msup></math></span> search significantly impacts search efficiency and schedule quality for automated manufacturing systems (AMSs). In Luo et al. (2015), two admissible heuristic functions were formulated for an A<span><math><msup><mrow></mrow><mrow><mo>∗</mo></mrow></msup></math></span> search based on place-timed PNs to schedule AMSs. To broaden its application scenarios and enhance search efficiency, this paper proposes a new heuristic function whose calculations take account of multiple resource acquisitions, weighted arcs, redundant resource units, and outdated resources, which are commonly encountered in practical AMSs but usually not considered. The proposed one can deal with generalized PNs, offering broader application scenarios than ordinary PNs. In addition, it is proven to be admissible and more informed than its counterparts, ensuring that the obtained schedules are optimal and making the timed PN-based A<span><math><msup><mrow></mrow><mrow><mo>∗</mo></mrow></msup></math></span> search more efficient. To validate the efficacy and efficiency of the proposed method, several benchmark systems are tested.</div></div>\",\"PeriodicalId\":10542,\"journal\":{\"name\":\"Computers & Operations Research\",\"volume\":\"175 \",\"pages\":\"Article 106912\"},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2024-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers & Operations Research\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0305054824003848\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Operations Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0305054824003848","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Scheduling AMSs with generalized Petri nets and highly informed heuristic search
The design of the heuristic function in a Petri-net(PN)-based A search significantly impacts search efficiency and schedule quality for automated manufacturing systems (AMSs). In Luo et al. (2015), two admissible heuristic functions were formulated for an A search based on place-timed PNs to schedule AMSs. To broaden its application scenarios and enhance search efficiency, this paper proposes a new heuristic function whose calculations take account of multiple resource acquisitions, weighted arcs, redundant resource units, and outdated resources, which are commonly encountered in practical AMSs but usually not considered. The proposed one can deal with generalized PNs, offering broader application scenarios than ordinary PNs. In addition, it is proven to be admissible and more informed than its counterparts, ensuring that the obtained schedules are optimal and making the timed PN-based A search more efficient. To validate the efficacy and efficiency of the proposed method, several benchmark systems are tested.
期刊介绍:
Operations research and computers meet in a large number of scientific fields, many of which are of vital current concern to our troubled society. These include, among others, ecology, transportation, safety, reliability, urban planning, economics, inventory control, investment strategy and logistics (including reverse logistics). Computers & Operations Research provides an international forum for the application of computers and operations research techniques to problems in these and related fields.