Yu Du, Fred Glover, Gary Kochenberger, Rick Hennig, Haibo Wang, Amit Hulandageri
{"title":"Solving the Minimum Sum Coloring Problem: Alternative Models, Exact Solvers, and Metaheuristics","authors":"Yu Du, Fred Glover, Gary Kochenberger, Rick Hennig, Haibo Wang, Amit Hulandageri","doi":"10.1287/ijoc.2022.0334","DOIUrl":"https://doi.org/10.1287/ijoc.2022.0334","url":null,"abstract":"<p>The minimum sum coloring problem (MSCP), a well-known NP-hard (nondeterministic polynomial time) problem with important practical applications, has been the subject of several papers in recent years. Because of the computational challenge posed by these problems, most solution methods employed are metaheuristics designed to find high-quality solutions with no guarantee of optimality. Exact methods (like Gurobi) and metaheuristic solvers have greatly improved in recent years, enabling high-quality and often optimal solutions to be found to a growing set of MSCPs. Alternative model forms can have a significant impact on the success of exact and heuristic methods in such settings, often providing enhanced performance compared with traditional model forms. In this paper, we introduce several alternative models for MSCP, including the quadratic unconstrained binary problem plus (QUBO-Plus) model for solving problems with constraints that are not folded into the objective function of the basic quadratic unconstrained binary problem (QUBO) model. We provide a computational study using a standard set of test problems from the literature that compares the general purpose exact solver from Gurobi with the leading QUBO metaheuristic solver NGQ and a special solver called Q-Card that belongs to the QUBO-Plus class. Our results highlight the effectiveness of the QUBO and QUBO-Plus models when solved with these metaheuristic solvers on this test bed, showing that the QUBO-Plus solver Q-Card provides the best performance for finding high-quality solutions to these important problems.</p><p><b>History:</b> Accepted by Pascal Van Hentenryck, Area Editor for Computational Modeling: Methods & Analysis.</p><p><b>Supplemental Material:</b> The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0334) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2022.0334). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/.</p>","PeriodicalId":13620,"journal":{"name":"Informs Journal on Computing","volume":"77 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141188213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yaqiong Wang, Junjie Wu, Zhiang Wu, Gediminas Adomavicius
{"title":"Efficient and Flexible Long-Tail Recommendation Using Cosine Patterns","authors":"Yaqiong Wang, Junjie Wu, Zhiang Wu, Gediminas Adomavicius","doi":"10.1287/ijoc.2022.0194","DOIUrl":"https://doi.org/10.1287/ijoc.2022.0194","url":null,"abstract":"INFORMS Journal on Computing, Ahead of Print. <br/>","PeriodicalId":13620,"journal":{"name":"Informs Journal on Computing","volume":"52 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140932854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christian Füllner, Peter Kirst, Hendrik Otto, Steffen Rebennack
{"title":"Feasibility Verification and Upper Bound Computation in Global Minimization Using Approximate Active Index Sets","authors":"Christian Füllner, Peter Kirst, Hendrik Otto, Steffen Rebennack","doi":"10.1287/ijoc.2023.0162","DOIUrl":"https://doi.org/10.1287/ijoc.2023.0162","url":null,"abstract":"INFORMS Journal on Computing, Ahead of Print. <br/>","PeriodicalId":13620,"journal":{"name":"Informs Journal on Computing","volume":"156 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140827383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Note from the Editor","authors":"Alice E. Smith","doi":"10.1287/ijoc.2024.ed.v36.n3","DOIUrl":"https://doi.org/10.1287/ijoc.2024.ed.v36.n3","url":null,"abstract":"INFORMS Journal on Computing, Ahead of Print. <br/>","PeriodicalId":13620,"journal":{"name":"Informs Journal on Computing","volume":"17 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140803290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christian Artigues, Emmanuel Hébrard, Alain Quilliot, Hélène Toussaint
{"title":"The Continuous Time-Resource Trade-off Scheduling Problem with Time Windows","authors":"Christian Artigues, Emmanuel Hébrard, Alain Quilliot, Hélène Toussaint","doi":"10.1287/ijoc.2022.0142","DOIUrl":"https://doi.org/10.1287/ijoc.2022.0142","url":null,"abstract":"INFORMS Journal on Computing, Ahead of Print. <br/>","PeriodicalId":13620,"journal":{"name":"Informs Journal on Computing","volume":"18 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140599795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hongzhao Guan, Beste Basciftci, Pascal Van Hentenryck
{"title":"Path-Based Formulations for the Design of On-demand Multimodal Transit Systems with Adoption Awareness","authors":"Hongzhao Guan, Beste Basciftci, Pascal Van Hentenryck","doi":"10.1287/ijoc.2023.0014","DOIUrl":"https://doi.org/10.1287/ijoc.2023.0014","url":null,"abstract":"<p>This paper reconsiders the On-Demand Multimodal Transit Systems (ODMTS) Design with Adoptions problem (ODMTS-DA) to capture the latent demand in on-demand multimodal transit systems. The ODMTS-DA is a bilevel optimization problem, for which Basciftci and Van Hentenryck proposed an exact combinatorial Benders decomposition. Unfortunately, their proposed algorithm only finds high-quality solutions for medium-sized cities and is not practical for large metropolitan areas. The main contribution of this paper is to propose a new path-based optimization model, called P-P<span>ath</span>, to address these computational difficulties. The key idea underlying P-P<span>ath</span> is to enumerate two specific sets of paths which capture the essence of the choice model associated with the adoption behavior of riders. With the help of these path sets, the ODMTS-DA can be formulated as a single-level mixed-integer programming model. In addition, the paper presents preprocessing techniques that can reduce the size of the model significantly. P-P<span>ath</span> is evaluated on two comprehensive case studies: the midsize transit system of the Ann Arbor – Ypsilanti region in Michigan (which was studied by Basciftci and Van Hentenryck) and the large-scale transit system for the city of Atlanta. The experimental results show that P-P<span>ath</span> solves the Michigan ODMTS-DA instances in a few minutes, bringing more than two orders of magnitude improvements compared with the existing approach. For Atlanta, the results show that P-P<span>ath</span> can solve large-scale ODMTS-DA instances (about 17 millions variables and 37 millions constraints) optimally in a few hours or in a few days. These results show the tremendous computational benefits of P-P<span>ath</span> which provides a scalable approach to the design of on-demand multimodal transit systems with latent demand.</p><p><b>History:</b> Accepted by Andrea Lodi, Design & Analysis of Algorithms—Discrete.</p><p><b>Funding:</b> This work was partially supported by National Science Foundation Leap-HI [Grant 1854684] and the Tier 1 University Transportation Center (UTC): Transit - Serving Communities Optimally, Responsively, and Efficiently (T-SCORE) from the U.S. Department of Transportation [69A3552047141].</p><p><b>Supplemental Material:</b> The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0014) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2023.0014). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/.</p>","PeriodicalId":13620,"journal":{"name":"Informs Journal on Computing","volume":"234 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140324325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniel Kowalczyk, Roel Leus, Christopher Hojny, Stefan Røpke
{"title":"A Flow-Based Formulation for Parallel Machine Scheduling Using Decision Diagrams","authors":"Daniel Kowalczyk, Roel Leus, Christopher Hojny, Stefan Røpke","doi":"10.1287/ijoc.2022.0301","DOIUrl":"https://doi.org/10.1287/ijoc.2022.0301","url":null,"abstract":"<p>We present a new flow-based formulation for identical parallel machine scheduling with a regular objective function and without idle time. The formulation is constructed with the help of a decision diagram that represents all job sequences that respect specific ordering rules. These rules rely on a partition of the planning horizon into, generally nonuniform, periods and do not exclude all optimal solutions, but they constrain solutions to adhere to a canonical form. The new formulation has numerous variables and constraints, and hence we apply a Dantzig-Wolfe decomposition to compute the linear programming relaxation in reasonable time; the resulting lower bound is stronger than the bound from the classical time-indexed formulation. We develop a branch-and-price framework that solves three instances from the literature for the first time. We compare the new formulation with the time-indexed and arc time–indexed formulation by means of a series of computational experiments.</p><p><b>History:</b> Accepted by Andrea Lodi, Area Editor for Design & Analysis of Algorithms—Discrete.</p><p><b>Funding:</b> This work was partially funded by the European Union’s Horizon 2020 research and innovation program under [Marie Skłodowska-Curie Grant 754462].</p><p><b>Supplemental Material:</b> The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0301) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2022.0301). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/.</p>","PeriodicalId":13620,"journal":{"name":"Informs Journal on Computing","volume":"31 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140315447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zachary Steever, Kyle Hunt, Mark Karwan, Junsong Yuan, Chase C. Murray
{"title":"A Graph-Based Approach for Relating Integer Programs","authors":"Zachary Steever, Kyle Hunt, Mark Karwan, Junsong Yuan, Chase C. Murray","doi":"10.1287/ijoc.2023.0255","DOIUrl":"https://doi.org/10.1287/ijoc.2023.0255","url":null,"abstract":"<p>This paper presents a framework for classifying and comparing instances of integer linear programs (ILPs) based on their mathematical structure. It has long been observed that the structure of ILPs can play an important role in determining the effectiveness of certain solution techniques; those that work well for one class of ILPs are often found to be effective in solving similarly structured problems. In this work, the structure of a given ILP instance is captured via a graph-based representation, where decision variables and constraints are described by nodes, and edges denote the presence of decision variables in certain constraints. Using machine learning techniques for graph-structured data, we introduce two approaches for leveraging the graph representations for relating ILPs. In the first approach, a graph convolutional network (GCN) is used to classify ILP graphs as having come from one of a known number of problem classes. The second approach makes use of latent features learned by the GCN to compare ILP graphs to one another directly. As part of the latter approach, we introduce a formal measure of graph-based structural similarity. A series of empirical studies indicate strong performance for both the classification and comparison procedures. Additional properties of ILP graphs, namely, losslessness and permutation invariance, are also explored via computational experiments.</p><p><b>History:</b> Accepted by Pascal Van Hentenryck, Area Editor for Computational Modeling: Methods & Analysis.</p><p><b>Supplemental Material:</b> The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0255) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2023.0255). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/.</p>","PeriodicalId":13620,"journal":{"name":"Informs Journal on Computing","volume":"10 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140298406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}