{"title":"Cover-based inequalities for the single-source capacitated facility location problem with customer preferences","authors":"Christina Büsing , Markus Leitner , Sophia Wrede","doi":"10.1016/j.cor.2025.107082","DOIUrl":"10.1016/j.cor.2025.107082","url":null,"abstract":"<div><div>The <em>single-source capacitated facility location problem with customer preferences (SSCFLPCP)</em> is known to be strongly NP-hard. Computational tests imply that state-of-the-art solvers struggle with computing exact solutions. In this paper, we contribute two novel preprocessing methods which reduce the size of the considered integer programming formulation and introduce sets of valid inequalities which decrease the integrality gap. Each of the introduced results utilises structural synergies between capacity constraints and customer preferences in the SSCFLPCP. First, we derive two preprocessing methods where the first method fixes location variables and the second method fixes allocation variables. Afterwards, we study cover-based inequalities. Here, we first strengthen the well-known cover inequalities: when determining covers, we also consider demands of customers not in the cover that must be assigned to the covered facility if a customer in the cover is assigned to it. We further strengthen these inequalities by including information on the assignments of customers in a cover if they are not assigned to the covered facility. Afterwards, we derive a new family of valid inequalities, which expresses the relation of open facilities based on sets of customers covering a facility. We then discuss solution methods for the corresponding separation problems and, finally, test our results for two preference types in a computational study. Our results show a clear positive impact of the preprocessing methods and inequalities, in particular when preferences are defined by assignment costs.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"182 ","pages":"Article 107082"},"PeriodicalIF":4.1,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143892010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zongli Dai , Xiaoyue Gong , Jian-Jun Wang , Lejing Yu , Jim (Junmin) Shi
{"title":"Integrated robust scheduling for inpatient surgery and ambulatory surgery","authors":"Zongli Dai , Xiaoyue Gong , Jian-Jun Wang , Lejing Yu , Jim (Junmin) Shi","doi":"10.1016/j.cor.2025.107098","DOIUrl":"10.1016/j.cor.2025.107098","url":null,"abstract":"<div><div>Ambulatory surgery services are becoming more and more popular as they can alleviate the shortage of hospital bed resources and increase the number of surgeries without increasing additional investment. In this mode, ambulatory surgery and inpatient surgery have different operating rooms but the same surgeons, which makes it difficult to coordinate the operating rooms and surgery time of the surgeon. In addition, the uncertainty of surgery duration and disruptions aggravate the difficulty of scheduling. Therefore, we model an integrated scheduling problem of ambulatory surgery and inpatient surgery under the in-hospital ambulatory surgery services mode. Considering the uncertainty of surgery duration and disruptions, a disruption management model based on distributionally robust optimization and machine learning consensus is established. For the computational complexity of the problem, we transform it into a two-stage robust problem and propose a disruption management algorithm to solve it. The experiment proves that integrated scheduling considering ambulatory surgery and inpatient surgery can significantly reduce the cost associated with the ORs and improve the utilization of the ORs. In addition, disruption management is not a once-and-for-all exercise, and the occurrence of new disruptions needs to be taken into account when performing disruption management.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"181 ","pages":"Article 107098"},"PeriodicalIF":4.1,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143887411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A heuristic algorithm with multi-scale perturbations for point arrangement and equal circle packing in a convex container","authors":"Xiangjing Lai , Jin-Kao Hao , Dong Yue , Yangming Zhou","doi":"10.1016/j.cor.2025.107099","DOIUrl":"10.1016/j.cor.2025.107099","url":null,"abstract":"<div><div>The point arrangement and equal circle packing problems are a category of classic max–min constrained optimization problems with many important applications. Being computationally very challenging to solve, they have been widely studied in operations research and mathematics. We propose a heuristic algorithm for the point arrangement and equal circle packing problems in various convex containers. The algorithm relies on several complementary search components, including an unconstrained optimization procedure that ensures diversified and intensified searches, an optima exploitation based adjustment method for the radius of circles, and a monotonic basin-hopping method with multi-scale perturbations. Computational results on numerous benchmark instances show that the proposed algorithm significantly outperforms the existing state-of-the-art algorithms, especially for hard instances or large-scale instances. For the well-known equal circle packing problem in a circular container, it improves the best-known result for 69 out of the 96 hardest instances widely used in the literature. For the majority of the remaining instances tested, the algorithm improves or matches the best-known results with a high success rate, despite of the fact that these instances have been tested by many existing algorithms. Experimental analysis shows that the optima exploitation based adjustment method for the radius of circles plays a crucial role for the high performance of the algorithm and that the multi-scale perturbations are able to significantly enhance the search ability and robustness of the algorithm. Given the general feature of the proposed framework, it can be applied to other related max–min constrained optimization problems.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"181 ","pages":"Article 107099"},"PeriodicalIF":4.1,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143882175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mingzhu Yu , Haoran Yang , Yaofeng Zhou , Xiaofan Lai , Gangqiao Wang
{"title":"International multimodal transportation optimization considering bulk cargo containerization","authors":"Mingzhu Yu , Haoran Yang , Yaofeng Zhou , Xiaofan Lai , Gangqiao Wang","doi":"10.1016/j.cor.2025.107095","DOIUrl":"10.1016/j.cor.2025.107095","url":null,"abstract":"<div><div>Bulk cargo containerization helps to reposition empty containers and reduce bulk cargo attrition in international trade. This paper studies an international multimodal transportation optimization problem that considers the containerization of bulk cargo in multiple planning periods. We provide a mathematical formulation for this optimization model, taking into account decisions related to equipment purchasing and bulk cargo containerization quantities. By incorporating the uncertainty of the bulk cargo demand, our basic model is extended to a two-stage stochastic mixed integer programming model. An improved Benders decomposition algorithm is proposed to solve this model. The results of numerical experiments and sensitivity analysis show that: (1) a high bulk cargo loss rate, a large number of nodes in the network, and an extensive planning period motivate carriers to pursue bulk cargo containerization; (2) when the price of the containerization equipment is reasonable, bulk cargo containerization can save costs; (3) the more complex the network, the higher the price of the equipment carriers can afford for bulk cargo containerization; and (4) considering uncertain demand with more demand scenarios can help reduce operational cost.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"182 ","pages":"Article 107095"},"PeriodicalIF":4.1,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143892011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Characteristics-based Estimation of distribution algorithm for the steelmaking-refining-continuous casting scheduling problem in the real-world steel plants","authors":"Long Zhang, Xi Hu, XiaoMing Wu","doi":"10.1016/j.cor.2025.107107","DOIUrl":"10.1016/j.cor.2025.107107","url":null,"abstract":"<div><div>As a key production process in the steel industry, excellent scheduling of Steelmaking-refining-Continuous Casting (SCC) manufacturing process can improve production efficiency, shorten the steel production cycle, and reduce the production cost for steel enterprises. This paper presents a Characteristics-based Estimation of Distribution Algorithm (CEDA) for the SCC scheduling problem in the real-world steel plants. Considering the processing characteristics of the continuous casting machine, a novel caster-based encoding scheme and an improved decoding scheme are proposed. Also, a distance concept is introduced to mitigate the impact of similar individuals on the probability model, and an importance-based probability model updating mechanism is designed to increase the impact of excellent individual on the probability model. Furthermore, an individual sampling scheme with enhanced probability is constructed to ensure continuous processing of the continuous casting machine as much as possible. Finally, this paper designs a limited insertion operation in the local search to address the exploitation of the proposed algorithm. Extensive numerical simulations demonstrate that the proposed CEDA for the SCC scheduling process is more efficient than some state-of-the-art algorithms in the literature.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"181 ","pages":"Article 107107"},"PeriodicalIF":4.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Dynamic inventory control and pricing strategies for perishable products considering both profit and waste","authors":"Melda Hasiloglu-Ciftciler , Onur Kaya","doi":"10.1016/j.cor.2025.107103","DOIUrl":"10.1016/j.cor.2025.107103","url":null,"abstract":"<div><div>With the increasing sustainability considerations throughout the world, there is an increasing interest in the effective management of perishable products both in the industry and the academia. There is a need to control the inventories, as well as the prices of perishable products in order to increase the profits while minimizing the waste. In this study, we focus on a retailer who sells old and new perishable food products, enabling demand shifts between products based on their prices and consumer behaviors. A bi-objective dynamic programming model is developed to optimize the discounted price, sale price, and order quantity of perishable food products in order to maximize the retailer’s profit and minimize food waste. We develop four static and dynamic pricing policies commonly practiced and quantify the advantages of dynamic pricing and price differentiation between old and new products in terms of both profit and waste. Our findings reveal that significant benefits can be obtained when the order quantity and the old product’s sale price decisions are given in a dynamic manner by considering the available inventory at hand. Additionally, this research analyzes the results of various weight combinations for profit and waste in the objective function. The findings highlight the significance of waste and sustainability concerns, underline the tradeoff between profit and waste and provide insights to companies to achieve improvements in their system results.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"181 ","pages":"Article 107103"},"PeriodicalIF":4.1,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143854650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jia Xu , Yuhang Han , Jian Liu , Nan Pan , Shi Yin , Weijie Liang , Wei Han , Cong Lin
{"title":"Investigation of the joint Automated mobile loading systems Two-Stage vehicle routing problem under the consideration of Supply-Demand Imbalance, fair Efficiency, and demand uncertainty","authors":"Jia Xu , Yuhang Han , Jian Liu , Nan Pan , Shi Yin , Weijie Liang , Wei Han , Cong Lin","doi":"10.1016/j.cor.2025.107108","DOIUrl":"10.1016/j.cor.2025.107108","url":null,"abstract":"<div><div>In supply chain management and emergency contexts, efficient and equitable material distribution is critical. Existing research remains underdeveloped in tackling issues like material shortages and demand uncertainty. This paper presents a novel two-stage vehicle routing method to address the imbalance between supply and demand of relief materials, such as food, and demand uncertainty during emergencies like wars and public health crises. By integrating an Automatic Mobile Loading (AML) system with vehicle collaborations in a two-stage routing problem, and using a Mixed Integer Linear Programming (MILP) model, this study optimizes the fairness and efficiency of material distribution. The study innovatively incorporates distance factors and demand uncertainty, proposing a fair and efficient distribution strategy. An improved Adaptive Large Neighborhood Search (ALNS) algorithm, hybridized with Tabu Search (TS) and incorporating Partial Sequence Dominance (PSD) and Exchange Strategy (ES), termed the ALNS/TPE algorithm, is designed to effectively solve the model problem through enhanced destruction and repair operators, greedy selection, and path segment exchange strategies. The improved algorithm demonstrates efficiency in small-scale test cases and superior performance in large-scale cases, generating low-cost solutions rapidly. In experiments conducted in Pudong, Shanghai, the enhanced algorithm reduced total costs by 11.2% compared to the traditional ALNS algorithm. Moreover, the AML-vehicle combination achieved a 37% reduction in total costs and a 42% saving in delivery time compared to single-vehicle distribution, significantly improving resource utilization and service quality.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"181 ","pages":"Article 107108"},"PeriodicalIF":4.1,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143878729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaoyu Chen , Tian Tian , Guangming Dai , Maocai Wang , Zhiming Song , Lining Xing
{"title":"Deep reinforcement learning-based resource allocation method for multi-satellite scheduling","authors":"Xiaoyu Chen , Tian Tian , Guangming Dai , Maocai Wang , Zhiming Song , Lining Xing","doi":"10.1016/j.cor.2025.107088","DOIUrl":"10.1016/j.cor.2025.107088","url":null,"abstract":"<div><div>Agile Earth observation satellites (AEOSs) scheduling represents a complex domain within combinatorial optimization, crucial for the regular operations and mission success of in-orbit satellites. In order to timelessly tackle the allocation of complex resources and corresponding time windows, a satellite resource adaptive allocation method, named SRADA-DRL, is proposed in this paper. By combining deep reinforcement learning (DRL) with rule-based heuristics, the SRADA-DRL is designed to optimize the allocation of satellite resources in dynamic environments. Concerning maximizing the total rewards of allocated missions, a mathematical model and a corresponding Markov decision model are constructed within the scheduling process. After analyzing the spatial–temporal distribution features of all resources and missions, the time-dependent missions are first decomposed into meta-missions corresponding to satellite resources, and a meta-mission is then selected to generate an allocation sequence in each stage. On this basis, the execution times for all missions are assigned in the single-satellite scheduling process. In which, the DRL updates the gradient information contingent upon the rewards garnered from the allocation sequence. In addition, the classical scheduling scenarios of varying scales are also conducted. Experimental results demonstrate the effectiveness and efficiency of the proposed SRADA-DRL method in addressing the AEOSs scheduling.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"181 ","pages":"Article 107088"},"PeriodicalIF":4.1,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143854652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Energy-efficient single-machine scheduling with group processing features under time-of-use electricity tariffs","authors":"Shuaipeng Yuan, Bailin Wang, Yihan Pei, Tieke Li","doi":"10.1016/j.cor.2025.107100","DOIUrl":"10.1016/j.cor.2025.107100","url":null,"abstract":"<div><div>This work studies a novel single machine scheduling problem with group-processing features under time-of-use tariffs, which is derived from the realistic hot milling process in modern steel manufacturing industry. The objective is to minimize the total energy cost while adhering to a bounded maximum completion time. We first propose two mixed integer linear programming (MILP) models: a time-indexed MILP and a period-based MILP. Next, we analyze the problem’s properties and design a block-based dynamic programming algorithm. To solve instances of practical size, an improved iterative greedy algorithm is introduced. In the algorithm, a problem-specific heuristic is presented to construct an initial solution. Both block-based and job-based disruption and reconstruction strategies, along with six local search operators, are designed to direct the algorithm towards promising regions. Moreover, a deep search strategy based on a 0–1 programming model is developed to optimize the sequence of jobs within each price interval. Computational results indicate that: (i) the efficiency of the period-based MILP is superior to the time-indexed MILP; (ii) the dynamic programming algorithm exhibits higher performance in solving some small-scale instances compared to the period-based MILP; and (iii) the proposed algorithm is highly effective for both small- and large- scale instances, which can provide effective support for the production management of enterprises.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"181 ","pages":"Article 107100"},"PeriodicalIF":4.1,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143851584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Adjusted distributionally robust bounds on expected loss functions","authors":"Yasemin Merzifonluoğlu , Joseph Geunes","doi":"10.1016/j.cor.2025.107081","DOIUrl":"10.1016/j.cor.2025.107081","url":null,"abstract":"<div><div>Optimization problems in operations and finance often include a cost that is proportional to the expected amount by which a random variable exceeds some fixed quantity, known as the expected loss function. Representation of this function often leads to computational challenges, depending on the distribution of the random variable of interest. Moreover, in practice, a decision maker may possess limited information about this probability distribution, such as the mean and variance, but not the exact form of the associated probability density or distribution function. In such cases, a distributionally robust (DR) optimization approach seeks to minimize the maximum expected cost among all possible distributions that are consistent with the available information. Past research has recognized the overly conservative nature of this approach because it accounts for worst-case probability distributions that almost surely do not arise in practice. Motivated by this, we propose a DR approach that accounts for the worst-case performance with respect to a broad class of common continuous probability distributions, while producing solutions that are less conservative (and, therefore, less expensive, on average) than those produced by existing DR approaches in the literature. The methods we propose also permit approximation of the expected loss function for probability distributions under which exact representation of the function is difficult or impossible. Finally, we draw a connection between Scarf-type bounds from the literature, and mean-MAD (mean absolute deviation) bounds when MAD information is available in addition to variance.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"181 ","pages":"Article 107081"},"PeriodicalIF":4.1,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143847779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}