Computers & Operations Research最新文献_第10页

Two-phase GRASP for the Multi-Constraint Graph Partitioning problem

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2024-12-12 DOI: 10.1016/j.cor.2024.106946

Alberto Herrán , J. Manuel Colmenar , Mauricio G.C. Resende

引用次数: 0

Feature and functional form selection in additive models via mixed-integer optimization

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2024-12-11 DOI: 10.1016/j.cor.2024.106945

Manuel Navarro-García , Vanesa Guerrero , María Durban , Arturo del Cerro

{"title":"Feature and functional form selection in additive models via mixed-integer optimization","authors":"Manuel Navarro-García , Vanesa Guerrero , María Durban , Arturo del Cerro","doi":"10.1016/j.cor.2024.106945","DOIUrl":"10.1016/j.cor.2024.106945","url":null,"abstract":"<div><div>Feature selection is a recurrent research topic in modern regression analysis, which strives to build interpretable models, using sparsity as a proxy, without sacrificing predictive power. The best subset selection problem is central to this statistical task: it has the goal of identifying the subset of covariates of a given size that provides the best fit in terms of an empirical loss function. In this work, we address the problem of feature and functional form selection in additive regression models under a mathematical optimization lens. Penalized splines (<span><math><mrow><mi>P</mi><mo>−</mo></mrow></math></span>splines) are used to estimate the smooth functions involved in the regression equation, which allow us to state the feature selection problem as a cardinality-constrained mixed-integer quadratic program (MIQP) in terms of both linear and non-linear covariates. To strengthen this MIQP formulation, we develop tight bounds for the regression coefficients. A matheuristic approach, which encompasses the use of a preprocessing step, the construction of a warm-start solution, the MIQP formulation and the large neighborhood search metaheuristic paradigm, is proposed to handle larger instances of the feature and functional form selection problem. The performance of the exact and the matheuristic approaches are compared in simulated data. Furthermore, our matheuristic is compared to other methodologies in the literature that have publicly available implementations, using both simulated and real-world data. We show that the stated approach is competitive in terms of predictive power and in the selection of the correct subset of covariates with the appropriate functional form. A public Python library is available with all the implementations of the methodologies developed in this paper.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"176 ","pages":"Article 106945"},"PeriodicalIF":4.1,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143165817","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}

引用次数: 0

A pharmaceutical distribution network considering supply cycles, waste, and inequity

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2024-12-11 DOI: 10.1016/j.cor.2024.106943

Paulina Kus Ariningsih , Chandra Ade Irawan , Antony Paulraj , Jing Dai

{"title":"A pharmaceutical distribution network considering supply cycles, waste, and inequity","authors":"Paulina Kus Ariningsih , Chandra Ade Irawan , Antony Paulraj , Jing Dai","doi":"10.1016/j.cor.2024.106943","DOIUrl":"10.1016/j.cor.2024.106943","url":null,"abstract":"<div><div>Perishable essential medicine products, especially in the context of developing countries, have suffered a challenge in terms of distribution budget. Moreover, distribution equity, sustainability, as well as replenishment cycles are critical characteristics for developing a careful and efficient distribution strategy for perishable medical products. To the best of our knowledge, this article is the first attempt to propose an optimisation model for the distribution network of perishable medical products by considering equity, supply waste, and replenishment cycle in the limited supply context. The proposed model is formulated as Mixed Integer Linear Programming (MILP) and solved using Variable Neighbourhood Search (VNS)-based matheuristic procedure. A new method referred to as the Learning VNS is developed as an alternative procedure to overcome the limitations of the current matheuristic approach. This approach endows the learning process for the exploration of the neighbourhood. To demonstrate practical employment, the proposed model and its solution method were applied to 12 instances in Indonesia’s COVID-19 contexts. The instances were developed under different thresholds of waste, inequity, and number of hubs. We found that the proposed model can effectively be solved through the proposed solution method. The computational experiments exhibit the attainability to develop an efficient distribution network with a consideration of waste and inequity. An outline of emerging research directions is presented in the last section of this article.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"176 ","pages":"Article 106943"},"PeriodicalIF":4.1,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166421","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}

引用次数: 0

Batch processing machine scheduling problems using a self-adaptive approach based on dynamic programming

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2024-12-10 DOI: 10.1016/j.cor.2024.106933

Yarong Chen , Xue Zhao , Jabir Mumtaz , Chen Guangyuan , Chen Wang

{"title":"Batch processing machine scheduling problems using a self-adaptive approach based on dynamic programming","authors":"Yarong Chen , Xue Zhao , Jabir Mumtaz , Chen Guangyuan , Chen Wang","doi":"10.1016/j.cor.2024.106933","DOIUrl":"10.1016/j.cor.2024.106933","url":null,"abstract":"<div><div>With the increasing trend of smart electronic devices, interlinked industries face various challenges in meeting market demand. The demand for customized small-batch and multi-variety products with agility in customer expectations makes the scheduling problem more complex. Batch-processing machine (BPM) scheduling refers to managing and organizing the execution of a group of tasks or jobs on a machine. BPM scheduling is a complex optimization problem critical in semiconductor production systems industries. A single BPM scheduling problem, considering multiple jobs with different sizes, release times, processing times, and due dates to minimize total earliness and tardiness, is studied in this paper. A mixed integer programming model is formulated to express the problem, including the related constraints. The self-adaptive hybrid differential evolution and tabu search (SDETS) algorithm with dynamic programming is proposed to solve the BPM-scheduling problem. The novel SDETS algorithm is embedded with four additional features: a) dynamic programming-based batch formation; b) right-left-shifting rules to identify the starting time of each batch; c) DE-self-adaptive mutation strategy to determine the job sequence and trade-off between exploration and exploitation; d) introduction of tabu-search to enhance the convergence rate. A comprehensive parametric tuning of the algorithms is conducted to optimize the performance and enhance the suitability for the specific problem set case instances. The findings suggest that the proposed algorithm surpasses the performance of the compared algorithms. Moreover, the SDETS method exhibits high convergence to find more precise and globally optimal solutions for large-scale problem instances, further emphasizing its practical applicability.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"176 ","pages":"Article 106933"},"PeriodicalIF":4.1,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143165833","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}

引用次数: 0

A method to identify a representation of the set of non-dominated points for discrete tri-objective optimization problems

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2024-12-09 DOI: 10.1016/j.cor.2024.106928

Sunney Fotedar, Ann-Brith Strömberg

{"title":"A method to identify a representation of the set of non-dominated points for discrete tri-objective optimization problems","authors":"Sunney Fotedar, Ann-Brith Strömberg","doi":"10.1016/j.cor.2024.106928","DOIUrl":"10.1016/j.cor.2024.106928","url":null,"abstract":"<div><div>Solving a discrete tri-objective optimization problem involves generating a set of non-dominated points. Most generation methods aim to identify all the non-dominated points to understand the trade-off between conflicting objectives. Finding all the non-dominated points is computationally demanding, which may discourage decision-makers from using generation methods that identify all the non-dominated points. Therefore, it is beneficial to identify a good representation of the Pareto front. In this work, we present an algorithm for computing a representation of the Pareto front for discrete tri-objective optimization problems for a user-defined coverage gap. Further, we present a parallelization approach to decompose the criterion space while avoiding redundancies. We present <em>constrained coverage gap</em> to measure performance of algorithms when the problems have incommensurable objective functions. Our algorithm is computationally compared with the state-of-the-art algorithms <em>Grid point based algorithm</em> (GPBA-A; Mesquita-Cunha et al., (2023) and <em>Territory-defining algorithm</em> (TDA; Ceyhan et al., (2019)). While our primary motivation comes from industrial applications of the generalized tri-objective tactical resource allocation problem (GTRAP; Fotedar et al., (2023)), we have also performed tests on standard benchmark instances of the multi-dimensional tri-objective knapsack problem (3KP) to further validate our approach. Out of 300 instances of 3KP, our proposed algorithm performs best (computationally) in 264 instances. For GTRAP, our algorithm is computationally superior in all the instances.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"176 ","pages":"Article 106928"},"PeriodicalIF":4.1,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166428","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}

引用次数: 0

Mixed-production flexible assembly job shop scheduling considering parallel assembly sequence variations under dual-resource constraints using multi-objective hybrid memetic algorithm

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2024-12-06 DOI: 10.1016/j.cor.2024.106932

Xin Lu, Cong Lu

{"title":"Mixed-production flexible assembly job shop scheduling considering parallel assembly sequence variations under dual-resource constraints using multi-objective hybrid memetic algorithm","authors":"Xin Lu, Cong Lu","doi":"10.1016/j.cor.2024.106932","DOIUrl":"10.1016/j.cor.2024.106932","url":null,"abstract":"<div><div>In this study, a mixed-production flexible assembly job shop scheduling considering parallel assembly sequence variations under dual-resource constraints (MFAJSS-PASV-DRC) is proposed, to achieve simultaneous optimization of part processing sequence and assembly sequence in mixed-production. By analyzing the MFAJSS-PASV-DRC problem, an integrated mathematical model that considers the interactive effects between part processing sequence and assembly sequence under dual-resource constraints in mixed-production is established, with the optimization objectives to minimize the total production completion time, the total inventory time, and the total labor cost during the production process. Based on the above, a multi-objective hybrid memetic algorithm (MoHMA) is proposed to solve the MFAJSS-PASV-DRC. In MoHMA, a four-layer segmented hybrid chromosome encoding structure is designed, then a mixed initialization strategy (MIX3) is applied to obtain a population of high quality, and two evolutionary methods are used to generate offspring chromosomes. Meanwhile, a variable neighborhood search (VNS) incorporating five local search methods is designed to prevent MoHMA from being stuck into a local optimum. The effectiveness of MIX3 and VNS are verified by an ablation experiment. Then an elite retention strategy is used to improve the quality of non-dominated solutions. In the case study, the Taguchi method is applied to obtain the best combination of parameters for the MoHMA algorithm. After that, the superiority of the proposed MFAJSS-PASV-DRC in improving production efficiency is verified, and the effectiveness of MoHMA is verified in solving the MFAJSS-PASV-DRC problem with different scales by comparing with other algorithms.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"176 ","pages":"Article 106932"},"PeriodicalIF":4.1,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143165825","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}

引用次数: 0

Data-driven robust flexible personnel scheduling

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2024-12-06 DOI: 10.1016/j.cor.2024.106935

Zilu Wang , Zhixing Luo , Huaxiao Shen

{"title":"Data-driven robust flexible personnel scheduling","authors":"Zilu Wang , Zhixing Luo , Huaxiao Shen","doi":"10.1016/j.cor.2024.106935","DOIUrl":"10.1016/j.cor.2024.106935","url":null,"abstract":"<div><div>Personnel scheduling in various industries often faces challenges due to unpredictable workloads. This paper focuses on the general flexible personnel scheduling problem at the operational level, which is characterized by uncertain demand and limited knowledge of the true distribution of this demand. To address this issue, we propose a distributionally robust model that utilizes the Wasserstein ambiguity set. This model is designed to maintain service levels across the worst-case distribution scenarios of random demand. In addition, we introduce a robust satisficing model that is oriented towards specific targets, offering practical applicability in real-world situations. Both models leverage empirical distributions derived from historical data, enabling the generation of robust personnel schedules that are responsive to uncertain demand, even when data availability is limited. We demonstrate that these robust models can be transformed into tractable counterparts. Moreover, we develop an exact depth-first search algorithm for identifying feasible daily schedules. Through a comprehensive case study and experiments using real-world data, we showcase the effectiveness and advantages of our proposed models and algorithms. The robustness of our models is thoroughly evaluated, providing valuable management insights and demonstrating their ability to tackle scheduling challenges in uncertain environments.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"176 ","pages":"Article 106935"},"PeriodicalIF":4.1,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166462","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}

引用次数: 0

Equity-driven facility location: A two-stage robust optimization approach

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2024-11-30 DOI: 10.1016/j.cor.2024.106920

Amin Ahmadi Digehsara , Menglei Ji , Amir Ardestani-Jaafari , Hoda Bidkhori

引用次数: 0

Graph neural networks for job shop scheduling problems: A survey

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2024-11-29 DOI: 10.1016/j.cor.2024.106914

Igor G. Smit , Jianan Zhou , Robbert Reijnen , Yaoxin Wu , Jian Chen , Cong Zhang , Zaharah Bukhsh , Yingqian Zhang , Wim Nuijten

{"title":"Graph neural networks for job shop scheduling problems: A survey","authors":"Igor G. Smit , Jianan Zhou , Robbert Reijnen , Yaoxin Wu , Jian Chen , Cong Zhang , Zaharah Bukhsh , Yingqian Zhang , Wim Nuijten","doi":"10.1016/j.cor.2024.106914","DOIUrl":"10.1016/j.cor.2024.106914","url":null,"abstract":"<div><div>Job shop scheduling problems (JSSPs) represent a critical and challenging class of combinatorial optimization problems. Recent years have witnessed a rapid increase in the application of graph neural networks (GNNs) to solve JSSPs, albeit lacking a systematic survey of the relevant literature. This paper aims to thoroughly review prevailing GNN methods for different types of JSSPs and the closely related flow-shop scheduling problems (FSPs), especially those leveraging deep reinforcement learning (DRL). We begin by presenting the graph representations of various JSSPs, followed by an introduction to the most commonly used GNN architectures. We then review current GNN-based methods for each problem type, highlighting key technical elements such as graph representations, GNN architectures, GNN tasks, and training algorithms. Finally, we summarize and analyze the advantages and limitations of GNNs in solving JSSPs and provide potential future research opportunities. We hope this survey can motivate and inspire innovative approaches for more powerful GNN-based approaches in tackling JSSPs and other scheduling problems.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"176 ","pages":"Article 106914"},"PeriodicalIF":4.1,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166461","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}

引用次数: 0

A literature review of reinforcement learning methods applied to job-shop scheduling problems 强化学习方法应用于作业车间调度问题的文献综述

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2024-11-27 DOI: 10.1016/j.cor.2024.106929

Xiehui Zhang, Guang-Yu Zhu

引用次数: 0