Yongliang Lu , Jin-Kao Hao , Qinghua Wu , Mingjie Li
{"title":"Frequent pattern mining driven evolutionary search for cross-dock door assignment","authors":"Yongliang Lu , Jin-Kao Hao , Qinghua Wu , Mingjie Li","doi":"10.1016/j.cor.2026.107393","DOIUrl":"10.1016/j.cor.2026.107393","url":null,"abstract":"<div><div>Capacitated cross-dock door assignment and uncapacitated cross-dock door assignment are two critical and challenging problems in supply chain management. This paper presents the first frequent pattern mining driven evolutionary algorithm to effectively solve these problems. The proposed approach incorporates a specialized data mining technique designed to extract significant frequent patterns from a collection of high-quality solutions, thereby guiding the search process. It also incorporates an efficient two-phase local optimization method that intensively inspects a given region to identify high-quality solutions, along with a quality-and-distance updating rule to manage the population of solutions. We evaluate the effectiveness of the proposed algorithm on popular benchmark instances of both problems. In particular, we report 26 improved best results (new upper bounds) out of 99 benchmark instances for the capacitated case and 25 improved best results out of 40 benchmark instances for the uncapacitated case. In addition, we show the importance of the two main search components, i.e., frequent pattern mining and local optimization. This research highlights the benefits of a collaboration between optimization algorithms and data mining methods. The code for our proposed algorithm will be made publicly available.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"189 ","pages":"Article 107393"},"PeriodicalIF":4.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976355","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}
Feng-Shun Zhou , Rong Hu , Wen-Bing Zhang , Bin Qian , Zi-Qi Zhang , Ling Wang
{"title":"Spatial decomposition-based variable neighborhood search algorithm for the integrated semiconductor backend production and distribution scheduling problem","authors":"Feng-Shun Zhou , Rong Hu , Wen-Bing Zhang , Bin Qian , Zi-Qi Zhang , Ling Wang","doi":"10.1016/j.cor.2026.107388","DOIUrl":"10.1016/j.cor.2026.107388","url":null,"abstract":"<div><div>To enhance the supply chain responsiveness of semiconductor enterprises, this study addresses the integrated semiconductor back-end production and distribution scheduling problem (ISBPDSP). To this end, a mixed-integer programming (MIP) model is formulated for the first time to minimize the total cost. Based on the ISBPDSP’s characteristics, four differentiated encoding–decoding schemes are designed to try to reduce both machine idle times and distribution distances, thereby decreasing each solution’s objective value as much as possible. To efficiently solve the considered problem, a novel space decomposition-based variable neighborhood search (SDVNS) algorithm is proposed to perform parallel search in the entire solution space. The SDVNS is a general variable neighborhood search (VNS) framework applicable to any of the above encoding–decoding schemes. In this framework, the space decomposition (SD) method is utilized to reasonably decompose the solution space into multiple subspaces, and an iterative search consisting of small-neighborhood exploration and four-stage large-neighborhood exploitation is developed to execute broad and in-depth search in each subspace. Experimental results demonstrate that the proposed SDVNS outperforms state-of-the-art algorithms in terms of both solution quality and computational efficiency.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"189 ","pages":"Article 107388"},"PeriodicalIF":4.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976354","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":"Multilevel iterated tabu search for the multi-constraint graph partitioning problem","authors":"Zhi Lu , Linlin Chen , Jian Gao , Jin-Kao Hao","doi":"10.1016/j.cor.2026.107389","DOIUrl":"10.1016/j.cor.2026.107389","url":null,"abstract":"<div><div>The multi-constraint graph partitioning (MCGP) problem involves partitioning a set of vertices into nonempty, pairwise-disjoint subsets such that each subset must satisfy certain bound constraints while minimizing the total cost of edges with both endpoints in the same subset. Arising from an integrated vehicle and pollster problem in a real-world application, MCGP generalizes a number of other well-known graph partitioning problems. Due to its NP-hard nature, solving MCGP is computationally challenging. This work presents the first multilevel iterated tabu search (MITS) algorithm to tackle MCGP. Specifically, the algorithm uses a problem-specific coarsening method to reduce progressively the input graph and relies on a dedicated feasible-and-infeasible iterated tabu search procedure to refine the solution to each reduced graph. Extensive experiments on two sets of 665 benchmark instances demonstrate that MITS significantly outperforms state-of-the-art algorithms by finding 573 new upper bounds, while matching 83 previous best-known upper bounds. We also apply the algorithm to another related graph partitioning problem to demonstrate its broader applicability. Additionally, we conduct analysis studies on key algorithmic components to verify the effectiveness of the proposed ideas and strategies.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"189 ","pages":"Article 107389"},"PeriodicalIF":4.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976359","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}
Héctor G.-de-Alba , Andrés Téllez , José Emmanuel Gómez-Rocha , Cipriano Santos , Juán Antonio Orozco , Ricardo Baeza-Yates
{"title":"Towards a trade-off of interpretability, accuracy and scalability: Enhanced formulations in linear classification models","authors":"Héctor G.-de-Alba , Andrés Téllez , José Emmanuel Gómez-Rocha , Cipriano Santos , Juán Antonio Orozco , Ricardo Baeza-Yates","doi":"10.1016/j.cor.2026.107411","DOIUrl":"10.1016/j.cor.2026.107411","url":null,"abstract":"<div><div>Transparency and interpretability are important topics within the machine learning community, particularly concerning the impact on decision makers of these technologies. These aspects are crucial for enabling users to leverage their expertise and decide whether to trust these technologies. In ML methods and particularly in the binary classification task, sparse linear methods have been developed and used as scoring systems. However, beyond their accuracy, we want these models to be sparse, with integer coefficients, and manipulable to allow the incorporation of operational constraints. These are known as Interpretable Machine Learning (IML) models for linear classification, where mathematical integer programming emerges as a tool to generate these IML models. Nonetheless, using integer programming generates models that are difficult to solve for large data sets. Consequently, motivated by the aforementioned issues, in this paper we propose new IML models for linear classification, based on two models: the Supersparse Linear Integer Model (SLIM) and Discrete Level Support Vector Machine (DILSVM). This new approach explores modeling the <span><math><msub><mrow><mi>L</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> function through the use of SOS1 constraints. Additionally, a “neural network style” approach is used to approximate the <span><math><msub><mrow><mi>L</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> function, where auxiliary variables and constraints are used to emulate an artificial neural network. Computational experiments conducted on a set of selected ML datasets demonstrate that our formulation has comparable accuracy and interpretability, but offers higher scalability.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"189 ","pages":"Article 107411"},"PeriodicalIF":4.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074710","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":"An adaptive large neighborhood decomposition search-based approach for the location-routing problem with pickup facilities and heterogeneous demands","authors":"Zhaofang Mao , Yida Xu , Enyuan Fu","doi":"10.1016/j.cor.2026.107398","DOIUrl":"10.1016/j.cor.2026.107398","url":null,"abstract":"<div><div>In last-mile delivery, the flexibility and heterogeneity of customer demands have driven package delivery companies to implement more adaptive strategies, such as utilizing pickup points and lockers. However, selecting optimal locations for these pickup points or lockers can be challenging due to various factors. To address these challenges, we propose the location-routing problem with pickup facilities and heterogeneous demands (LRP-PFHD). To solve this problem, we formulate a mixed integer linear programming (MILP) model to minimize the total cost. We adapt the adaptive large neighborhood decomposition search (ALNDS) algorithm by incorporating initial solution generation strategies to improve solution quality and efficiency. Furthermore, we conduct a comprehensive computational study to verify the effectiveness and efficiency of our proposed method. The results show that this distribution mode could give a total cost-saving of about 9.97%–42.40% compared to the conventional CVRP mode. Finally, we carry out a case study in Vienna, Graz, and Linz and conduct a sensitivity analysis to provide managerial insights.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"189 ","pages":"Article 107398"},"PeriodicalIF":4.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146035853","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 hybrid genetic search for the inventory routing problem","authors":"Bruno Castro , Marcus Poggi , Rafael Martinelli","doi":"10.1016/j.cor.2025.107376","DOIUrl":"10.1016/j.cor.2025.107376","url":null,"abstract":"<div><div>The Inventory Routing Problem (IRP), an essential component of supply chain management, involves efficiently managing deliveries from a depot to clients using a fleet of vehicles. Recognized in a recent international challenge, the IRP requires innovative approaches. This paper presents a Hybrid Genetic Search (HGS) algorithm, with a distinctive crossover operation tailored for IRP and a fast way to calculate optimal inventory levels using network flows on an auxiliary graph. Our method integrates HGS with the Network Simplex IRP decoder, combined with a refined solution constructor, efficient IRP and Capacitated Vehicle Routing Problem local searches, and several components that make the hybrid framework effective for the IRP. We provide an extensive computational evaluation, showing that our algorithm outperforms 22 recent methods from the literature, providing 137 new best-known solutions for a classical instance set and 180 new best-known solutions for a recent larger instance set. Moreover, according to the rules of the recent international challenge, our method would rank first.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"189 ","pages":"Article 107376"},"PeriodicalIF":4.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146035851","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":"Production-logistics cooperative scheduling in a two-stage assembly flow-shop with deteriorating robotic arm: a problem-specific heuristic","authors":"Wenyu Zhang, Zihao Luo, Shuai Zhang","doi":"10.1016/j.cor.2026.107409","DOIUrl":"10.1016/j.cor.2026.107409","url":null,"abstract":"<div><div>The application of autonomous mobile robots (AMRs) in smart workshops has significantly enhanced automation levels and fostered a closer integration between production and logistics. However, existing research on the two-stage assembly flow-shop often overlooks the role of transportation resources within intra-logistics. This study addresses the gap by investigating a bi-objective two-stage assembly flow-shop scheduling problem considering two types of AMRs and robotic arm deterioration (TAFSP-AMRs). A novel mathematical model is formulated to minimize both makespan and total energy consumption. To solve the problem, both exact and heuristic methods are adopted. For small-scale problems, the <span><math><mrow><mi>ε</mi><mo>-</mo></mrow></math></span> constraint method is used to transform the bi-objective model into a series of mono-objective models, which are then solved exactly using the GUROBI solver. Since GUROBI is ineffective for large-scale problems, a new problem-specific heuristic algorithm that can also reliably generate a specified number of solutions is proposed based on the properties of the TAFSP-AMRs. In our experiment, the results confirm the proposed model’s validity, while comprehensive evaluations demonstrate the heuristic algorithm’s reliable performance across multiple metrics.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"189 ","pages":"Article 107409"},"PeriodicalIF":4.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074709","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}
Nicolás Cabrera, Jean-François Cordeau, Jorge E. Mendoza
{"title":"A survey of workforce scheduling and routing problems","authors":"Nicolás Cabrera, Jean-François Cordeau, Jorge E. Mendoza","doi":"10.1016/j.cor.2025.107344","DOIUrl":"10.1016/j.cor.2025.107344","url":null,"abstract":"<div><div>The workforce scheduling and routing problem (WSRP) involves assigning geographically dispersed tasks to workers and planning their routes to complete these tasks efficiently. This problem arises in numerous real-world scenarios, including technicians conducting preventive maintenance at customer sites, nurses providing home care, and security guards patrolling multiple locations. To address these challenges, researchers have incorporated a wide range of constraints, such as time windows, skill compatibility, and team composition. In this survey, we systematically structure and analyze the WSRP literature, identifying its core characteristics and uncovering key research gaps. Our findings highlight critical areas for future investigation, including the integration of multi-modal routes and precedence constraints. Additionally, we emphasize practical features that should guide the development of new solution methods for this family of problems, ensuring their applicability to real-world workforce management challenges.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"189 ","pages":"Article 107344"},"PeriodicalIF":4.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074711","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}
Francisco Yuraszeck , Gonzalo Mejía , Daniel Alejandro Rossit , Armin Lüer-Villagra
{"title":"A note on “A constraint programming-based lower bounding procedure for the job shop scheduling problem”","authors":"Francisco Yuraszeck , Gonzalo Mejía , Daniel Alejandro Rossit , Armin Lüer-Villagra","doi":"10.1016/j.cor.2026.107396","DOIUrl":"10.1016/j.cor.2026.107396","url":null,"abstract":"<div><div>In Yuraszeck et al. (2025), we recently proposed a constraint programming (CP) lower-bounding procedure for the minimal makespan job shop scheduling problem (JSSP). This approach consisted of two phases: in the first phase, a relaxation of the original problem is solved, while in the second phase, this relaxation is iteratively tightened until a time limit is reached or no better bounds are found. In this paper, we introduce a third phase, that iteratively solves the subproblems left unaddressed in the second phase. Additionally, we evaluate the influence of <em>warm-starting</em> the algorithm on solution quality and computational time. We tested our updated procedure on 80 <em>open</em> JSSP instances, finding 14 new lower bounds with an average reduction in the optimality gap of 29.59% compared with the best-known bounds from the literature.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"189 ","pages":"Article 107396"},"PeriodicalIF":4.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146035850","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":"Humanitarian relief logistics network design considering facility location, inventory pre-positioning and evacuation planning: A two-stage distributionally robust optimization approach","authors":"Tao Zhang , Shuaian Wang , Xu Xin","doi":"10.1016/j.cor.2026.107390","DOIUrl":"10.1016/j.cor.2026.107390","url":null,"abstract":"<div><div>The high uncertainty in the occurrence, space, and scale of natural disasters presents significant challenges to reliable humanitarian relief logistics network (HRLN) design. After a disaster occurs, relief supplies and evacuees are usually transported simultaneously through the HRLN, which occupies limited logistics infrastructure (i.e., roads). This phenomenon drives the integration of three crucial decisions in the design of HRLNs: the emergency facility locations, the pre-positioning of the relief inventory, and the human evacuation planning. This composite problem is formulated as a two-stage distributionally robust optimization model, with the two stages corresponding to pre-disaster and post-disaster decision-making. To capture the characteristics of the distribution functions of the number of evacuees and the road capacity, we design an ambiguity set using historical data and the type-1 Wasserstein metric. We show that there is an equivalent reformulation of the abovementioned model that can be solved by decomposition algorithms. Two versions of the decomposition algorithm, i.e., single-cut and multi-cut versions, are developed based on the generic Benders-decomposition technique. A case study is conducted on the Yushu earthquake in China and several managerial implications are proposed.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"189 ","pages":"Article 107390"},"PeriodicalIF":4.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146035852","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}