Computers & Operations Research最新文献

{"title":"A soft encoding-based evolutionary algorithm for the steelmaking scheduling problem and its extension under energy thresholds","authors":"Sheng-Long Jiang","doi":"10.1016/j.cor.2024.106885","DOIUrl":"10.1016/j.cor.2024.106885","url":null,"abstract":"<div><div>Steelmaking and continuous casting scheduling problem (SCCSP) is a classic optimization problem increasingly incorporating more constraints, such as energy-related ones. However, classic evolutionary algorithms with “rigid” encoding schemes face challenges in finding optimal solutions for heavily constrained SCCSPs. Motivated by this gap, this paper first extends the mathematical model of the classic SCCSP to its variant under energy thresholds (ET-SCCSP) from both single- and multi-objective optimization perspectives, and derives several problem-specific properties. Next, this paper develops a solving algorithm named the soft encoding-based evolutionary algorithm (SoEA), which uses a real-valued vector to encode a feasible solution for SCCSPs. Furthermore, SoEA introduces the following components: (1) a peak-cutting backward list scheduling (PC-BLS) procedure to decode a real-valued vector into a feasible solution, and (2) a local search procedure to enhance the algorithm’s performance. Comparative results in the computational experiment demonstrate that the SoEA with the propose encoding/decoding scheme: (1) achieves better performance than exact solver for small-scale instances under energy thresholds, (2) obtains promising results for medium-scale instances compared to other schemes, and (3) can be intensified by the tailored local search procedure. The proposed SoEA can also serve as a benchmark or tutorial for the development and evaluation of high-efficiency algorithms for other SCCSPs with heavy constraints. The source code is available on the GitHub repository: <span><span>https://github.com/janason/Soft-Scheduling/tree/master/SoEA</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"174 ","pages":"Article 106885"},"PeriodicalIF":4.1,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142704701","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":"Arc-flow formulation and branch-and-price-and-cut algorithm for the bin-packing problem with fragile objects","authors":"Sunkanghong Wang,&nbsp;Shaowen Yao,&nbsp;Hao Zhang,&nbsp;Qiang Liu,&nbsp;Lijun Wei","doi":"10.1016/j.cor.2024.106878","DOIUrl":"10.1016/j.cor.2024.106878","url":null,"abstract":"<div><div>This study introduces an arc-flow formulation and the first branch-and-price-and-cut (BPC) algorithm designed to solve the bin-packing problem with fragile objects (BPPFO). This variant of the bin-packing problem originates in the field of telecommunications, particularly in the allocation of cellular calls to frequency channels. The arc-flow formulation is inspired by previous studies and modifies the graph construction method to accommodate fragility constraints. We proved the correctness of this formulation and demonstrated its superiority in instances with small maximum fragility through extensive experiments. The proposed BPC algorithm leverages advanced cutting and packing techniques and incorporates innovative elements such as problem reduction, additional cutting planes, and a label-setting-based exact pricing algorithm. The experimental results demonstrate that the proposed BPC algorithm is highly competitive with the state-of-the-art algorithm for solving the BPPFO and can successfully solve several previously unsolved instances.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"173 ","pages":"Article 106878"},"PeriodicalIF":4.1,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553258","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":"Cross regional online food delivery: Service quality optimization and real-time order assignment","authors":"Farhana Huq ,&nbsp;Nahar Sultana ,&nbsp;Palash Roy ,&nbsp;Md. Abdur Razzaque ,&nbsp;Shamsul Huda ,&nbsp;Mohammad Mehedi Hassan","doi":"10.1016/j.cor.2024.106877","DOIUrl":"10.1016/j.cor.2024.106877","url":null,"abstract":"<div><div>Online food delivery (OFD) represents a rapidly evolving e-business application that leverages cloud computing data centers, playing a crucial role in meeting the demands of urban lifestyles. With diverse order fulfillment features and increasing expectations for service quality, the task of effectively assigning riders for timely long-distance, cross-regional deliveries presents a significant engineering challenge. Previous studies often relied on traditional rider allocation methods that fail to account for varying capacities, or they utilized non-intelligent systems that did not adequately address fluctuating order demands and service delays. In this study, we introduce a robust Mixed Integer Linear Programming (MILP) optimization framework designed to minimize the total service time and delivery cost for cross-regional orders. This framework divides a large OFD area into multiple regions and utilizes both transfer vehicles and riders to optimize deliveries. To enhance the predictive accuracy of our model, we incorporate advanced machine learning techniques. Specifically, we employ the Long Short-Term Memory (LSTM) model to forecast regional order demands accurately, reflecting the dynamic nature of the marketplace. Additionally, Extreme Gradient Boosting (XGBoost) is tailored to dynamically predict travel times from restaurants to customer locations, facilitating more precise scheduling and resource allocation within the MILP framework. These machine learning techniques significantly bolster the MILP framework by providing detailed, accurate predictions that improve decision-making processes and adaptability to real-time conditions. Acknowledging the complexity of this optimization problem, we further enhance our approach by integrating a meta-heuristic algorithm, Adaptive Large Neighbor Search (ALNS), which efficiently assigns orders to the appropriate transfer vehicles and riders within polynomial time. Our Cross Regional Online Food Delivery (XROFD) system is meticulously designed to optimize both customer satisfaction and rider incentives. Simulation experiments confirm that the XROFD system not only reduces service times and delivery costs but also markedly enhances customer satisfaction and provides superior incentives for riders, outperforming existing state-of-the-art methods.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"173 ","pages":"Article 106877"},"PeriodicalIF":4.1,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553259","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":"Algorithms for the global domination problem","authors":"Ernesto Parra Inza ,&nbsp;Nodari Vakhania ,&nbsp;José María Sigarreta Almira ,&nbsp;Frank Ángel Hernández Mira","doi":"10.1016/j.cor.2024.106876","DOIUrl":"10.1016/j.cor.2024.106876","url":null,"abstract":"<div><div>A dominating set <span><math><mi>D</mi></math></span> in a graph <span><math><mi>G</mi></math></span> is a subset of its vertices such that every its vertex that does not belong to set <span><math><mi>D</mi></math></span> is adjacent to at least one vertex from set <span><math><mi>D</mi></math></span>. A set of vertices of graph <span><math><mi>G</mi></math></span> is a global dominating set if it is a dominating set for both, graph <span><math><mi>G</mi></math></span> and its complement. The objective is to find a global dominating set with the minimum cardinality. Neither exact nor approximation algorithm existed for the problem known to be <span><math><mrow><mi>N</mi><mi>P</mi></mrow></math></span>-hard. We show that it remains <span><math><mrow><mi>N</mi><mi>P</mi></mrow></math></span>-hard for restricted types of graphs. At the same time, we specify some families of graphs for which the three heuristics, that we propose here, are optimal. Given the complexity status of the problem, our aim was the development of powerful heuristic algorithms that work well in practice for large-scaled instances. To measure the efficiency of our heuristics, we formulated the problem as an integer linear program (ILP) and also we developed an alternative implicit enumeration (IE) algorithm obtaining guaranteed optimal solutions for the existing benchmark instances with up to 8000 vertices. Remarkably, for 56.75% of these instances, at least one of our heuristics also created an optimal solution, where an average absolute error for the remaining instances was a single vertex. The average approximation ratio was 1.005, whereas for the largest benchmark instances with up to 25000 vertices our heuristics delivered solutions in less than 2 min.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"173 ","pages":"Article 106876"},"PeriodicalIF":4.1,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553257","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":"Novel mathematical formulations for parallel-batching processing machine scheduling problems","authors":"Shaoxiang Zheng ,&nbsp;Naiming Xie ,&nbsp;Qiao Wu ,&nbsp;Caijie Liu","doi":"10.1016/j.cor.2024.106859","DOIUrl":"10.1016/j.cor.2024.106859","url":null,"abstract":"<div><div>We study mathematical formulations for batch-processing machine scheduling problems (BPMPs), which are the challenging issues in the machine scheduling literature where machines are capable of processing a batch of jobs simultaneously if jobs with non-identical sizes can be packed in a capacitated machine. In this paper, we tackle single- and parallel-machine BPMPs, and other interesting problem variants that aim at minimizing the makespan. We develop novel formulations along with valid inequalities and an algorithm framework that makes use of dual information and bounding techniques to achieve efficiency when instances are intractable. Extensive computational experiments on benchmark instances show that our approaches achieve state-of-the-art results and prove the optimality of intractable instances in the literature.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"173 ","pages":"Article 106859"},"PeriodicalIF":4.1,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572184","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":"The quadratic knapsack problem with setup","authors":"Laura Galli ,&nbsp;Silvano Martello ,&nbsp;Carlos Rey ,&nbsp;Paolo Toth","doi":"10.1016/j.cor.2024.106873","DOIUrl":"10.1016/j.cor.2024.106873","url":null,"abstract":"<div><div>The Quadratic Knapsack Problem is a well-known generalization of the classical 0-1 knapsack problem, in which any pair of items produces a pairwise profit if both are selected. Another relevant generalization of the knapsack problem is the Knapsack Problem with Setup, in which the items are partitioned into classes, the items of a class can only be inserted into the knapsack if the corresponding class is activated, and activating a class involves a setup cost and a setup capacity reduction.</div><div>Despite a rich literature on these two problems, their obvious generalization, i.e., the Quadratic Knapsack Problem with Setup, was never investigated so far. We discuss applications, mathematical models, deterministic matheuristic algorithms, and computationally evaluate their performance.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"173 ","pages":"Article 106873"},"PeriodicalIF":4.1,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142536185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Satellite Scheduling Problems: A survey of applications in Earth and outer space observation","authors":"Benedetta Ferrari ,&nbsp;Jean-François Cordeau ,&nbsp;Maxence Delorme ,&nbsp;Manuel Iori ,&nbsp;Roberto Orosei","doi":"10.1016/j.cor.2024.106875","DOIUrl":"10.1016/j.cor.2024.106875","url":null,"abstract":"<div><div>With the growing interest in leveraging space technologies to provide both knowledge and services, the need for efficient space mission management also increases. Among all the related problems, the scheduling of tasks performed by observation satellites is not only crucial for the astrophysical community, but it also poses challenging optimization problems, which have been studied for nearly 30 years. The aim of this survey is to provide a comprehensive overview of Satellite Scheduling Problems (SSPs), with a particular focus on applications. First, we propose a novel literature classification of SSPs based on the main variants that have been defined over the years. We address both imaging and communication tasks in the context of Earth-centered missions and, for the first time, of outer space missions. Then, for each class of problems we provide a review of the main contributions available in the literature, offering insights about solution methodologies. Finally, we outline some promising future research directions.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"173 ","pages":"Article 106875"},"PeriodicalIF":4.1,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stochastic bilevel interdiction for fake news control in online social networks","authors":"Kati Moug ,&nbsp;Siqian Shen","doi":"10.1016/j.cor.2024.106872","DOIUrl":"10.1016/j.cor.2024.106872","url":null,"abstract":"<div><div>Social media platforms attempt to mitigate and control fake news, using interventions such as flagging posts or adjusting newsfeed algorithms, to protect vulnerable individuals. In this paper, we consider performing intervention actions on specific source nodes or user–user edges in social networks, under uncertain effectiveness of different intervention strategies. We model misinformation from malicious users to vulnerable communities using stochastic network interdiction formulations. Specifically, we minimize the expected number of reachable vulnerable users via stochastic maximum flow, and develop an alternative formulation for handling large-scale social networks based on their topological structures. We derive theoretical results for path-based networks and develop an approximate algorithm for single-edge removal on paths. We test instances of a social network with 23,505 nodes, based on the IMDb actors dataset, to demonstrate the scalability of the approach and its effectiveness. Via numerical studies, we find that characteristics of removed edges change when intervention effectiveness is stochastic. Our results suggest that intervention should target on (i) a smaller set of centrally located edges with nodes that represent communities where regulatory actions are more effective, and (ii) dispersed edges with nodes where intervention has a high chance of failure.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"173 ","pages":"Article 106872"},"PeriodicalIF":4.1,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142536183","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":"Distributionally robust optimization of a newsvendor model under capital constraint and risk aversion","authors":"Jia Zhai ,&nbsp;Hui Yu ,&nbsp;Kai-Rong Liang ,&nbsp;Kevin W. Li","doi":"10.1016/j.cor.2024.106870","DOIUrl":"10.1016/j.cor.2024.106870","url":null,"abstract":"<div><div>This paper proposes a capital-constrained newsvendor model with risk aversion under a partially known demand distribution with only knowledge of its mean and variance. We adopt the robust conditional value-at-risk (RCVaR) to characterize the vendor’s risk aversion. Firstly, we obtain the closed-form RCVaR optimal order quantity that depends on the demand volatility level: When demand volatility is low, the vendor has four financing-ordering strategies contingent upon different capital levels. When demand volatility is medium, the vendor does not seek bank loans and is left with two ordering strategies. When demand volatility is high, the vendor does not bother placing an order at all. Then, we investigate the impact of capital constraint, risk aversion and demand volatility on the RCVaR optimal order quantity. Finally, we demonstrate the robustness of the RCVaR optimal ordering policy by numerical experiments based on both randomly generated and real-world data.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"173 ","pages":"Article 106870"},"PeriodicalIF":4.1,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553256","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":"Customer order scheduling on a serial-batch machine in precast bridge construction","authors":"Gang Liu ,&nbsp;Yong Xie ,&nbsp;Hongwei Wang","doi":"10.1016/j.cor.2024.106871","DOIUrl":"10.1016/j.cor.2024.106871","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":4.1,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142536184","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}