{"title":"Customer order scheduling on a serial-batch machine in precast bridge construction","authors":"Gang Liu , Yong Xie , Hongwei Wang","doi":"10.1016/j.cor.2024.106871","DOIUrl":null,"url":null,"abstract":"<div><div>Prefabricated construction is widely adopted in the current bridge construction project, especially offshore bridges. The realistic requirements of large quantities of prefabricated parts and tight delivery schedules make it extremely challenging to develop optimal scheduling. We address a new customer order scheduling on a serial-batch machine (COS-SBM) to reduce the sum of inventory holding costs of finished jobs and tardiness costs of orders in precast bridge construction. In the COS-SBM problem, all jobs with incompatibility in orders need to be divided into batches, which are then scheduled for processing on a serial-batch machine. We develop a mixed-integer linear programming model to formulate this new problem. Since the COS-SBM problem is NP-hard, we propose a genetic algorithm based on a novel batch sequencing and forming encoding method (GA-BSFE), which makes the scheduling and batching decisions simultaneously to enhance its exploration. Moreover, we design an efficient three-stage heuristic based on the order weighted modified due date rule and batch weighted longest processing time rule. The three-stage heuristic is introduced into the initiation of GA-BSFE to enhance its exploitation. Finally, a set of instances generated based on the realistic production of precast girders is tested to validate the effectiveness of GA-BSFE. The performance analysis suggests that GA-BSFE is the most appropriate for the COS-SBM problem.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"173 ","pages":"Article 106871"},"PeriodicalIF":4.1000,"publicationDate":"2024-10-16","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/S0305054824003435","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}
引用次数: 0
Abstract
Prefabricated construction is widely adopted in the current bridge construction project, especially offshore bridges. The realistic requirements of large quantities of prefabricated parts and tight delivery schedules make it extremely challenging to develop optimal scheduling. We address a new customer order scheduling on a serial-batch machine (COS-SBM) to reduce the sum of inventory holding costs of finished jobs and tardiness costs of orders in precast bridge construction. In the COS-SBM problem, all jobs with incompatibility in orders need to be divided into batches, which are then scheduled for processing on a serial-batch machine. We develop a mixed-integer linear programming model to formulate this new problem. Since the COS-SBM problem is NP-hard, we propose a genetic algorithm based on a novel batch sequencing and forming encoding method (GA-BSFE), which makes the scheduling and batching decisions simultaneously to enhance its exploration. Moreover, we design an efficient three-stage heuristic based on the order weighted modified due date rule and batch weighted longest processing time rule. The three-stage heuristic is introduced into the initiation of GA-BSFE to enhance its exploitation. Finally, a set of instances generated based on the realistic production of precast girders is tested to validate the effectiveness of GA-BSFE. The performance analysis suggests that GA-BSFE is the most appropriate for the COS-SBM problem.
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.