Proceedings of the International Symposium on Combinatorial Search
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Proceedings of the International Symposium on Combinatorial Search

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Explore the latest research and advancements in combinatorial search algorithms and techniques. Discover cutting-edge solutions from the International Symposium proceedings.

Proceedings of the International Symposium on Combinatorial Search Cover

Articles in this Journal

From Agent Centric to Obstacle Centric Planning: A Makespan-Optimal Algorithm for the Multi-Agent Warehouse Rearrangement Problem

The Multi-Agent Warehouse Rearrangement (MAWR) problem calls for computing agents plans such that they collectively rearrange a warehouse environment from a given layout which species the location of every movable obstacle in the environment, to a go...

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From Scalable SAT to MaxSAT: Massively Parallel Solution Improving Search

Maximum Satisfiability (MaxSAT) is an essential framework for combinatorial optimization at the core of automated reasoning. However, to date, no notable parallelizations with convincing scaling behaviour exist. We suggest to exploit and transfer rec...

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Lazy Heuristic Search for Solving POMDPs with Expensive-to-Compute Belief Transitions

Heuristic search solvers like RTDP-Bel and LAO* have proven effective for computing optimal and bounded sub-optimal solutions for Partially Observable Markov Decision Processes (POMDPs), which are typically formulated as belief MDPs. A belief represe...

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Lightweight and Effective Preference Construction in PIBT for Large-Scale Multi-Agent Pathfinding

PIBT is a computationally lightweight algorithm that can be applied to a variety of multi-agent pathfinding (MAPF) problems, generating the next collision-free locations of agents given another. Because of its simplicity and scalability, it is becomi...

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Hierarchical DeepPruner: A Novel Framework for Search Space Reduction

Combinatorial optimization (CO) problems on graphs arise in various applications across diverse domains. Many of these problems are NP-hard, and heuristics have been developed to provide near-optimal solutions. In the big data era, the high dimension...

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Low-Level Search on Time Intervals in Branch-and-Cut-and-Price for Multi-Agent Path Finding

Multi-agent path finding is the problem of navigating a set of agents from their starting locations to their target locations while avoiding collisions. A leading method for optimal multi-agent path finding is branch-and-cut-and-price, a framework ba...

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Minimizing Fuel in Multi-Agent Pathfinding

The multi-agent pathfinding problem (MAPF) of finding conflict-free paths for multiple agents has attracted a large number of researchers in the past. The cost of the solution is commonly measured by the sum-of-costs (SOC) cost function or, less comm...

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Efficient Primal Heuristics for Mixed Binary Quadratic Programs Using Suboptimal Rounding Guidance

Mixed Binary Quadratic Programs (MBQPs) are a class of NP-hard problems that arise in a wide range of applications, including finance, machine learning, and chemical and energy systems. Large-scale MBQPs are challenging to solve with exact algorithms...

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A Preprocessing Framework for Efficient Approximate Bi-Objective Shortest-Path Computation in the Presence of Correlated Objectives

The bi-objective shortest-path (BOSP) problem seeks to find paths between start and target vertices of a graph while optimizing two conflicting objective functions. We consider the BOSP problem in the presence of correlated objectives. Such correlati...

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A Bucket-Based Priority Queue for Bounded-Suboptimal and Anytime A* Search

We introduce a priority queue data structure, called a bucket heap, which generalizes the bucket queue commonly used to accelerate A* search for shortest-path problems with a small range of integer transition costs. Unlike a bucket queue, a bucket he...

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New Mechanisms in Flex Distribution for Bounded Suboptimal Multi-Agent Path Finding

Multi-Agent Path Finding (MAPF) is the problem of finding a set of collision-free paths, one for each agent in a shared environment. Its objective is to minimize the sum of path costs (SOC), where the path cost of each agent is defined as the travel...

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Sub-Microsecond Grid Path Planning, at What Cost?

Tree Cache is a lightweight pre-processing approach to grid path finding which works by generating a shortest path tree: from a root cell to all cells in the map. During online search Tree Cache simply follows the tree: from start and target towards...

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A Problem with the Current Methodology for Comparing Search Algorithms and a Proposed Solution

This paper explores how incompletely described tie-break policies can invalidate the experimental results reported in papers on optimal bidirectional heuristic search (BiHS). Experiments usually use a single implementation of an algorithm with its sp...

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Finding All Optimal Solutions in Multi-Agent Path Finding

The Multi-Agent Path Finding problem (MAPF) aims to find conflict-free paths for a group of agents, leading each agent to its respective goal. MAPF is applicable in navigating autonomous robots and vehicles to their destination. In this paper, we stu...

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Sorting Colored Balls in Colored Tubes

We consider a game that was played in a German television show that is similar to the sorting balls puzzle. In it, we are assumed to move one colored ball after another in a set of colored tubes so that in the end, each ball is in the tube of its col...

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