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Symposium on Combinatorial Search最新文献

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Real-World Pickup and Delivery Problem with Transfers 现实世界中的接送问题
Symposium on Combinatorial Search Pub Date : 2023-07-02 DOI: 10.1609/socs.v16i1.27286
Václav Sobotka, Hana Rudová
{"title":"Real-World Pickup and Delivery Problem with Transfers","authors":"Václav Sobotka, Hana Rudová","doi":"10.1609/socs.v16i1.27286","DOIUrl":"https://doi.org/10.1609/socs.v16i1.27286","url":null,"abstract":"The pickup and delivery problem with transfers generalizes the classical pickup and delivery problem (PDP) by allowing the vehicles to exchange request loads at designated transfer points. Transfers often lead to substantial reductions in transportation costs, yet they come with a significant burden of additional computational complexity. Even meta-heuristic methods are thus limited to instances of at most lower hundreds of requests leaving the desirable benefits unreachable for larger instances. Our approach bypasses the complexities inherent to current methods by deciding about the transfers apriori and thus reducing the problem to a PDP instance. To make as informed decisions as possible, we analyze a broader set of characteristics that may be used to carry out the apriori decisions. We opt to derive and examine multiple such PDP instances to cover different transfer choices. Our analysis of the derived PDP instances then allows their efficient processing in parallel. The proposed framework addresses a large-scale freight transportation problem with real-world characteristics and transfers where typical instances count over 1,200 requests and 300 vehicles. We show the potential of the proposed framework on both real-world and synthetic instances with up to 1,500 requests. The experiments demonstrate that substantial savings may be achieved within favorable runtimes even for very large instances.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124191164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Adapting to Planning Failures in Lifelong Multi-Agent Path Finding 多智能体终身寻径中规划失败的适应
Symposium on Combinatorial Search Pub Date : 2023-07-02 DOI: 10.1609/socs.v16i1.27282
Jonathan Morag, Roni Stern, Ariel Felner
{"title":"Adapting to Planning Failures in Lifelong Multi-Agent Path Finding","authors":"Jonathan Morag, Roni Stern, Ariel Felner","doi":"10.1609/socs.v16i1.27282","DOIUrl":"https://doi.org/10.1609/socs.v16i1.27282","url":null,"abstract":"Multi-Agent Path Finding (MAPF) is the problem of finding collision-free paths for multiple agents operating in the same environment. In Lifelong MAPF (LMAPF), these agents continuously receive new destinations, and the task is to constantly update their paths while optimizing for a high throughput over time. Therefore, many MAPF sub-problems must be solved over time in order to solve a single LMAPF problem. LMAPF problems manifest in real-world applications, such as automated warehouses, where strict responsiveness requirements limit the amount of time allocated to planning. MAPF algorithms occasionally fail to produce a plan within the allotted time. We propose a system design for LMAPF that is robust to such planning failures. Then, we explore different approaches to avoid planning failures, reduce their severity, and handle them when they occur. In particular, we describe and analyze different Fail Policies that are applied when planning failures occur and ensure collisions and unnecessary degradation of throughput are avoided. To our knowledge, while such Fail Policies are used in practice in the industry, they have yet to be researched academically.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128527848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Efficient Multi Agent Path Finding with Turn Actions 有效的多代理路径查找与回合行动
Symposium on Combinatorial Search Pub Date : 2023-07-02 DOI: 10.1609/socs.v16i1.27290
Yue Zhang, Daniel D. Harabor, P. L. Bodic, P. J. Stuckey
{"title":"Efficient Multi Agent Path Finding with Turn Actions","authors":"Yue Zhang, Daniel D. Harabor, P. L. Bodic, P. J. Stuckey","doi":"10.1609/socs.v16i1.27290","DOIUrl":"https://doi.org/10.1609/socs.v16i1.27290","url":null,"abstract":"Current approaches for real-world Multi-Agent Path Finding (MAPF) usually start with a simplified MAPF model and modify the resulting plans so they are kinematically feasible. We investigate one such problem, called MAPF with turn actions MAPF_T, and show that ignoring the kinematic constraints significantly increases solution cost. A first modification of the popular Conflict-Based Search algorithm to MAPF_T yields significantly better plans but comes at the cost of substantial decreases in scalability. We then introduce several techniques that can improve the performance of CBS for MAPF_T, including stronger and generalised versions of existing symmetry-breaking constraints and a novel pruning technique that eliminates redundant branches in the CBS constraint tree. Experimental results on six popular MAPF domains show convincing improvements for CBS success rate and substantial reductions in node expansions and runtime.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129067410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Greedy Priority-Based Search for Suboptimal Multi-Agent Path Finding 基于贪心优先级的次优多智能体寻路算法
Symposium on Combinatorial Search Pub Date : 2023-07-02 DOI: 10.1609/socs.v16i1.27278
Shao-Hung Chan, Roni Stern, Ariel Felner, Sven Koenig
{"title":"Greedy Priority-Based Search for Suboptimal Multi-Agent Path Finding","authors":"Shao-Hung Chan, Roni Stern, Ariel Felner, Sven Koenig","doi":"10.1609/socs.v16i1.27278","DOIUrl":"https://doi.org/10.1609/socs.v16i1.27278","url":null,"abstract":"Multi-Agent Path Finding (MAPF) is the problem of finding collision-free paths, one for each agent, in a shared environment, while minimizing their sum of travel times. Since solving MAPF optimally is NP-hard, researchers have explored algorithms that solve MAPF suboptimally but efficiently. Priority-Based Search (PBS) is the leading algorithm for this purpose. It finds paths for individual agents, one at a time, and resolves collisions by assigning priorities to the colliding agents and replanning their paths during its search. However, PBS becomes ineffective for MAPF instances with high densities of agents and obstacles. Therefore, we introduce Greedy PBS (GPBS), which uses greedy strategies to speed up PBS by minimizing the number of collisions between agents. We then propose techniques that speed up GPBS further, namely partial expansions, target reasoning, induced constraints, and soft restarts. We show that GPBS with all these improvements has a higher success rate than the state-of-the-art suboptimal algorithm for a 1-minute runtime limit, especially for MAPF instances with small maps and dense obstacles.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115967767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Domain Specific Situated Planning (Student Abstract) 特定领域定位规划(学生摘要)
Symposium on Combinatorial Search Pub Date : 2023-07-02 DOI: 10.1609/socs.v16i1.27315
D. Thomas
{"title":"Domain Specific Situated Planning (Student Abstract)","authors":"D. Thomas","doi":"10.1609/socs.v16i1.27315","DOIUrl":"https://doi.org/10.1609/socs.v16i1.27315","url":null,"abstract":"Traditionally when planning we assume that we receive the problem instance as input, then formulate a plan, then the clock begins and the agent executes the plan. Sometimes we are forced to consider time passing as we plan, which is known as situated planning. In my dissertation I explore situated planning in three domains: grid based path planning, the orienteering problem and opportunistic science.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116769992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
On K* Search for Top-K Planning 关于K*搜索Top-K规划
Symposium on Combinatorial Search Pub Date : 2023-07-02 DOI: 10.1609/socs.v16i1.27281
Junkyu Lee, Michael Katz, Shirin Sohrabi
{"title":"On K* Search for Top-K Planning","authors":"Junkyu Lee, Michael Katz, Shirin Sohrabi","doi":"10.1609/socs.v16i1.27281","DOIUrl":"https://doi.org/10.1609/socs.v16i1.27281","url":null,"abstract":"Finding multiple high-quality plans is essential in many planning applications, and top-k planning asks for finding the k best plans, naturally extending cost-optimal classical planning. Several attempts have been made to formulate top-k classical planning as a k-shortest paths finding problem and apply K* search, which alternates between A* and Eppstein's algorithm. However, earlier work had shortcomings, among which were failing to handle inconsistent heuristics and degraded performance in Eppstein's algorithm implementations. As a result, existing evaluation results severely underrate the performance of the K* based approach to top-k planning. In this paper, we present a new top-k planner based on a novel variant of K* search. We address the following three aspects. First, we show an alternative implementation of Eppstein's algorithm for classical planning, which resolves a major bottleneck in earlier attempts. Second, we present a new strategy for alternating A* and Eppstein's algorithm, that improves the performance of K* on the classical planning benchmarks. Last, we introduce a simple mitigation of the limitation of K* to tasks with a single goal state, allowing us to preserve heuristic informativeness in face of imposed task reformulation. Empirical evaluation results show that the proposed approach achieves the state-of-the-art performance on the classical planning benchmarks. The code is available at https://github.com/IBM/kstar.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133091926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Improved Exploration of the Bench Transition System in Parallel Greedy Best First Search 基于并行贪心最优优先搜索的改进板凳过渡系统探索
Symposium on Combinatorial Search Pub Date : 2023-07-02 DOI: 10.1609/socs.v16i1.27285
Takumi Shimoda, A. Fukunaga
{"title":"Improved Exploration of the Bench Transition System in Parallel Greedy Best First Search","authors":"Takumi Shimoda, A. Fukunaga","doi":"10.1609/socs.v16i1.27285","DOIUrl":"https://doi.org/10.1609/socs.v16i1.27285","url":null,"abstract":"While parallelization of A* is fairly well-understood, parallelization of GBFS has been much less understood. Recent work has proposed PUHF, a parallel GBFS which restricts search to exploration of the Bench Transition System (BTS), which is the set of states that can be expanded by GBFS under some tie-breaking policy. However, PUHF causes threads to spend much of the time waiting so that only states which are guaranteed to be in the BTS are expanded. We propose improvements to PUHF which significantly reduce idle time and allow more rapid exploration of the BTS, resulting in better search performance.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133244480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Towards an Effective Framework Combining Planning and Scheduling [Extended Abstract] 构建计划与调度相结合的有效框架[扩展摘要]
Symposium on Combinatorial Search Pub Date : 2023-07-02 DOI: 10.1609/socs.v16i1.27300
Andrii Nyporko, L. Chrpa
{"title":"Towards an Effective Framework Combining Planning and Scheduling [Extended Abstract]","authors":"Andrii Nyporko, L. Chrpa","doi":"10.1609/socs.v16i1.27300","DOIUrl":"https://doi.org/10.1609/socs.v16i1.27300","url":null,"abstract":"In a nutshell, Automated Planning deals with finding sequences of actions that achieve a required goal while scheduling deals with allocating activities on (limited) resources meeting specified constraints. Activities, however, might resemble actions in planning as we might capture what they can produce and under what conditions. That said, the \"planning'' part represents selecting proper activities as well as their ordering which the \"scheduling'' part represents allocating the activities to the resources.\u0000This extended abstract formalises the concept of \"combined\" planning and scheduling tasks and proposes the idea how these tasks can be compiled to classical planning tasks. Our idea is evaluated on tasks involving scheduling activities on reconfigurable machines.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130708084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
On the Notion of Fixability of PDDL+ Plans [Extended Abstract] 关于PDDL+方案的可修复性的概念[扩展摘要]
Symposium on Combinatorial Search Pub Date : 2023-07-02 DOI: 10.1609/socs.v16i1.27302
Francesco Percassi, Enrico Scala, M. Vallati
{"title":"On the Notion of Fixability of PDDL+ Plans [Extended Abstract]","authors":"Francesco Percassi, Enrico Scala, M. Vallati","doi":"10.1609/socs.v16i1.27302","DOIUrl":"https://doi.org/10.1609/socs.v16i1.27302","url":null,"abstract":"PDDL+ is an expressive formalism that allows for the use of planning in hybrid discrete-continuous domains. To cope with unexpected situations, it is crucial for deployed planning-based systems to efficiently repair existing plans. In this paper, we revisit a recently proposed FIXABILITY framework for expressing and solving problems from validation to rescheduling of actions in PDDL+ plans.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123610876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Search Algorithms for Multi-Agent Teamwise Cooperative Path Finding [Extended Abstract] 多智能体团队协作寻径的搜索算法[扩展摘要]
Symposium on Combinatorial Search Pub Date : 2023-07-02 DOI: 10.1609/socs.v16i1.27304
Z. Ren, S. Rathinam, H. Choset
{"title":"Search Algorithms for Multi-Agent Teamwise Cooperative Path Finding [Extended Abstract]","authors":"Z. Ren, S. Rathinam, H. Choset","doi":"10.1609/socs.v16i1.27304","DOIUrl":"https://doi.org/10.1609/socs.v16i1.27304","url":null,"abstract":"Multi-Agent Path Finding (MA-PF) finds collision-free paths for multiple agents from their respective start to goal locations. This paper investigates a generalization of MA-PF called Multi-Agent Teamwise Cooperative Path Finding (MA-TC-PF), where agents are grouped as multiple teams and each team has its own objective to minimize. In general, there is more than one team, and MA-TC-PF is thus a multi-objective planning problem with the goal of finding the entire Pareto-optimal front that represents all possible trade-offs among the objectives of the teams. We show that the existing CBS and M* for MA-PF can be modified to solve MA-TC-PF, which is verified with tests. We discuss the conditions under which the proposed algorithms are complete and are guaranteed to find the Pareto-optimal front for MA-TC-PF.","PeriodicalId":425645,"journal":{"name":"Symposium on Combinatorial Search","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122578491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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