{"type":"ScholarlyArticle","title":"Large Neighborhood Search with Decision Diagrams","authors":[{"name":"Xavier Gillard","slug":"xavier-gillard","given":"Xavier","family":"Gillard","affiliation":"Université Catholique de Louvain , BELGIUM"},{"name":"Pierre Schaus","slug":"pierre-schaus","given":"Pierre","family":"Schaus","affiliation":"Université Catholique de Louvain , BELGIUM"}],"abstract":"Local search is a popular technique to solve combinatorial\r\noptimization problems efficiently. To escape local minima one generally uses\r\nmetaheuristics or try to design large neighborhoods around the current best\r\nsolution. A somewhat more black box approach consists in using an\r\noptimization solver to explore a large neighborhood. This is the\r\nlarge-neighborhood search (LNS) idea that we reuse in this work. We\r\nintroduce a generic neighborhood exploration algorithm based on restricted\r\ndecision diagrams (DD) constructed from the current best\r\nsolution. We experiment DD-LNS on two sequencing problems: the\r\ntraveling salesman problem with time windows (TSPTW) and a production\r\nplanning problem (DLSP). Despite its simplicity, DD-LNS is competitive with\r\nthe state-of-the-art MIP approach on DLSP. It is able to improve the\r\nbest known solutions of some standard instances for TSPTW and even to prove \r\nthe optimality of quite a few other instances.","doi":"10.24963/ijcai.2022/659","url":"https://ijcai.org/proceedings/2022/659","pdf":"https://ijcai.org/proceedings/2022/0659.pdf","markdown":"https://ijcai.org/proceedings/2022/659.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/659","volume":{"slug":"2022","title":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2022","url":"https://ijcai.org/proceedings/2022/","year":2022,"location":"Vienna","dates":"23-29 July 2022","editors":"Luc De Raedt","isbn":"978-1-956792-00-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2022"},"section":"Search","track":"Main Track","number":659,"pages":{"first":4754,"last":4760},"keywords":["Constraint Satisfaction and Optimization: Solvers and Tools","Constraint Satisfaction and Optimization: Constraint Optimization","Search: Meta-Reasoning and Meta-Heuristics","Search: Combinatorial Search and Optimisation"],"videos":[{"label":"Video #1","url":"https://slideslive.com/38987122","length_sec":85,"provider":"slideslive"},{"label":"Video #2","url":"https://slideslive.com/38985265","length_sec":662,"provider":"slideslive"}],"references":[{"position":1,"raw":"[Ahuja et al., 2002] Ravindra K Ahuja, Özlem Ergun, James B Orlin, and Abraham P Punnen. A survey of very large-scale neighborhood search techniques. Discrete Ap- plied Mathematics, 123(1-3):75-102, 2002.","title":"A survey of very large-scale neighborhood search techniques","authors":"Özlem Ravindra K Ahuja, James B Ergun, Abraham P Orlin, Punnen","year":"2002","venue":"Discrete Applied Mathematics","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Bellman, 1954] Richard Bellman. The theory of dynamic programming. Bulletin of the American Mathematical So- ciety, 60(6):503-515, 11 1954.","title":"The theory of dynamic programming","authors":"Richard Bellman","year":"1954","venue":"Bulletin of the American Mathematical Society","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Bergman et al., 2016] David Bergman, Andre A. Cire, Willem-Jan van Hoeve, and J. N. Hooker. Discrete opti- mization with decision diagrams. INFORMS Journal on Computing, 28(1):47-66, 2016.","title":"Discrete optimization with decision diagrams","authors":"David Bergman, Andre A Cire, Willem-Jan Van Hoeve, J N Hooker","year":"2016","venue":"INFORMS Journal on Computing","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Björdal et al., 2020] Gustav Björdal, Pierre Flener, Justin Pearson, Peter J Stuckey, and Guido Tack. Solving satis- faction problems using large-neighbourhood search. In In- ternational Conference on Principles and Practice of Con- straint Programming, pages 55-71. Springer, 2020.","title":"Solving satisfaction problems using large-neighbourhood search","authors":"Björdal","year":"2020","venue":"International Conference on Principles and Practice of Constraint Programming","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Cire, 2014] Andre A Cire. Decision Diagrams for Opti- mization. PhD thesis, Carnegie Mellon University Tepper School of Business, 2014.","title":"Decision Diagrams for Optimization","authors":"Andre A Cire","year":"2014","venue":null,"doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Cormen et al., 2009] Thomas H Cormen, Charles E Leiser- son, Ronald L Rivest, and Clifford Stein. Introduction to algorithms. MIT press, 2009.","title":"Introduction to algorithms","authors":"Charles E Thomas H Cormen, Ronald L Leiserson, Clifford Rivest, Stein","year":"2009","venue":null,"doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Da Silva and Urrutia, 2010] Rodrigo Ferreira Da Silva and Sebastián Urrutia. A general vns heuristic for the traveling salesman problem with time windows. Discrete Optimiza- tion, 7(4):203-211, 2010.","title":"A general vns heuristic for the traveling salesman problem with time windows","authors":"Da Silva, Urrutia, Rodrigo Ferreira, Da Silva, Sebastián Urrutia","year":"2010","venue":"Discrete Optimization","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Demirović et al., 2018] Emir Demirović, Geoffrey Chu, and Peter J Stuckey. Solution-based phase saving for cp: A value-selection heuristic to simulate local search behavior in complete solvers. In International Conference on Prin- ciples and Practice of Constraint Programming, pages 99- 108. Springer, 2018.","title":"Solution-based phase saving for cp: A value-selection heuristic to simulate local search behavior in complete solvers","authors":"Demirović","year":"2018","venue":"International Conference on Principles and Practice of Constraint Programming","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Dumas et al., 1995] Yvan Dumas, Jacques Desrosiers, Eric Gelinas, and Marius M Solomon. An optimal algorithm for the traveling salesman problem with time windows. Operations research, 43(2):367-371, 1995.","title":"An optimal algorithm for the traveling salesman problem with time windows","authors":"Yvan Dumas, Jacques Desrosiers, Eric Gelinas, Marius M Solomon","year":"1995","venue":"Operations research","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Fischetti and Lodi, 2010] Matteo Fischetti and Andrea Lodi. Heuristics in mixed integer programming. Wiley Encyclopedia of Operations Research and Management Science, 2010.","title":"Heuristics in mixed integer programming","authors":"Matteo Fischetti, Andrea Lodi","year":"2010","venue":null,"doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Gent and Walsh, 1999] Ian P Gent and Toby Walsh. CSPLib: a benchmark library for constraints. In Inter- national Conference on Principles and Practice of Con- straint Programming, pages 480-481. Springer, 1999.","title":"CSPLib: a benchmark library for constraints","authors":"P Ian, Toby Gent, Walsh","year":"1999","venue":"International Conference on Principles and Practice of Constraint Programming","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Gillard et al., 2020] X.","title":null,"authors":"X","year":null,"venue":null,"doi":null,"url":null,"internal_url":null},{"position":13,"raw":"Gillard, P. Schaus, and V. Coppé. Ddo, a generic and efficient framework for mdd-based op- timization. International Joint Conference on Artificial In- telligence (IJCAI-20); DEMO track, 2020.","title":"Ddo, a generic and efficient framework for mdd-based optimization","authors":"P Gillard, V Schaus, Coppé","year":"2020","venue":"International Joint Conference on Artificial Intelligence (IJCAI-20); DEMO track","doi":null,"url":null,"internal_url":"/proceedings/2020/757"},{"position":14,"raw":"[Gillard et al., 2021] Xavier Gillard, Vianney Coppé, Pierre Schaus, and André Augusto Cire. Improving the filter- ing of branch-and-bound mdd solver. In Peter J. Stuckey, editor, Integration of Constraint Programming, Artificial Intelligence, and Operations Research, pages 231-247, Cham, 2021. Springer International Publishing.","title":"Improving the filtering of branch-and-bound mdd solver","authors":"Xavier Gillard, Vianney Coppé, Pierre Schaus, André Augusto, Cire","year":"2021","venue":"Integration of Constraint Programming, Artificial Intelligence, and Operations Research","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Gonzalez et al., 2020] Jaime E Gonzalez, Andre A Cire, Andrea Lodi, and Louis-Martin Rousseau. Integrated in- teger programming and decision diagram search tree with an application to the maximum independent set problem. Constraints, pages 1-24, 2020.","title":"Integrated integer programming and decision diagram search tree with an application to the maximum independent set problem","authors":"Jaime E Gonzalez, Andre A Cire, Andrea Lodi, Louis-Martin Rousseau","year":"2020","venue":"Constraints","doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Hentenryck and Michel, 2009] Pascal Van Hentenryck and Laurent Michel. Constraint-based local search. The MIT press, 2009.","title":"Constraint-based local search","authors":"Michel ; Hentenryck, Pascal Van Hentenryck, Laurent Michel","year":"2009","venue":null,"doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Hoos and Stützle, 2004] Holger H Hoos and Thomas Stützle. Stochastic local search: Foundations and applications. Elsevier, 2004.","title":"Stochastic local search: Foundations and applications","authors":"H Holger, Thomas Hoos, Stützle","year":"2004","venue":null,"doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[Jain and Van Hentenryck, 2011] Siddhartha Jain and Pascal Van Hentenryck. Large neighborhood search for dial-a- ride problems. In International Conference on Principles and Practice of Constraint Programming, pages 400-413. Springer, 2011.","title":"Large neighborhood search for dial-aride problems","authors":"Van Jain, Siddhartha Hentenryck, Pascal Jain, Van Hentenryck","year":"2011","venue":"International Conference on Principles and Practice of Constraint Programming","doi":null,"url":null,"internal_url":null},{"position":19,"raw":"[Laborie et al., 2018] Philippe Laborie, Jérôme Rogerie, Paul Shaw, and Petr Vilím. Ibm ilog cp optimizer for scheduling. Constraints, 23(2):210-250, 2018.","title":"Ibm ilog cp optimizer for scheduling","authors":"Philippe Laborie, Jérôme Rogerie, Paul Shaw, Petr Vilím","year":"2018","venue":"Constraints","doi":null,"url":null,"internal_url":null},{"position":20,"raw":"[Lin and Kernighan, 1973] Shen Lin and Brian W Kernighan. An effective heuristic algorithm for the traveling-salesman problem. Operations research, 21(2):498-516, 1973.","title":"An effective heuristic algorithm for the traveling-salesman problem","authors":"Shen Lin, Brian W Kernighan","year":"1973","venue":"Operations research","doi":null,"url":null,"internal_url":null},{"position":21,"raw":"[López-Ibáñez and Blum, 2010] Manuel López-Ibáñez and Christian Blum. Beam-aco for the travelling salesman problem with time windows. Computers & operations re- search, 37(9):1570-1583, 2010.","title":"Manuel López-Ibáñez and Christian Blum. Beam-aco for the travelling salesman problem with time windows","authors":"López-Ibáñez And Blum","year":"2010","venue":"Computers & operations research","doi":null,"url":null,"internal_url":null},{"position":22,"raw":"[Mingozzi et al., 1997] Aristide Mingozzi, Lucio Bianco, and Salvatore Ricciardelli. Dynamic programming strate- gies for the traveling salesman problem with time win- dow and precedence constraints. Operations research, 45(3):365-377, 1997.","title":"Dynamic programming strategies for the traveling salesman problem with time window and precedence constraints","authors":"Mingozzi","year":"1997","venue":"Operations research","doi":null,"url":null,"internal_url":null},{"position":23,"raw":"[Pipatsrisawat and Darwiche, 2007] Knot Pipatsrisawat and Adnan Darwiche. A lightweight component caching scheme for satisfiability solvers. In International confer- ence on theory and applications of satisfiability testing, pages 294-299. Springer, 2007.","title":"Knot Pipatsrisawat and Adnan Darwiche. A lightweight component caching scheme for satisfiability solvers","authors":"Darwiche Pipatsrisawat","year":"2007","venue":"International conference on theory and applications of satisfiability testing","doi":null,"url":null,"internal_url":null},{"position":24,"raw":"[Pochet and Wolsey, 2006] Yves Pochet and Laurence A. Wolsey. Production Planning by Mixed Integer Program- ming. Springer, 2006.","title":"Production Planning by Mixed Integer Programming","authors":"Yves Pochet, Laurence A Wolsey","year":"2006","venue":null,"doi":null,"url":null,"internal_url":null},{"position":25,"raw":"[Savelsbergh, 1985] Martin WP Savelsbergh. Local search in routing problems with time windows. Annals of Opera- tions research, 4(1):285-305, 1985.","title":"Local search in routing problems with time windows","authors":"W P Martin, Savelsbergh","year":"1985","venue":"Annals of Operations research","doi":null,"url":null,"internal_url":null},{"position":26,"raw":"[Shaw, 1998] Paul Shaw. Using constraint programming and local search methods to solve vehicle routing problems. In International conference on principles and practice of constraint programming, pages 417-431. Springer, 1998.","title":"Using constraint programming and local search methods to solve vehicle routing problems","authors":"Paul Shaw","year":"1998","venue":"International conference on principles and practice of constraint programming","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}