Papers Traveling Salesman Problem
“Traveling Salesman Problem” 태그가 달린 논문 254편 · 필터 해제
Multimodal Fused Learning for Solving the Generalized Traveling Salesman Problem in Robotic Task Planning
Effective and efficient task planning is essential for mobile robots, especially in applications like warehouse retrieval and environmental monitoring. These tasks often involve selecting one location from each of severa…
Computational EfficiencyTask PlanningTraveling Salesman ProblemRsGCN: Rescaling Enhances Generalization of GCNs for Solving Scalable Traveling Salesman Problems
Neural traveling salesman problem (TSP) solvers face two critical challenges: poor generalization for scalable TSPs and high training costs. To address these challenges, we propose a new Rescaling Graph Convolutional Net…
Traveling Salesman ProblemLearning for Dynamic Combinatorial Optimization without Training Data
We introduce DyCO-GNN, a novel unsupervised learning framework for Dynamic Combinatorial Optimization that requires no training data beyond the problem instance itself. DyCO-GNN leverages structural similarities across t…
Combinatorial OptimizationTraveling Salesman ProblemLMask: Learn to Solve Constrained Routing Problems with Lazy Masking
Routing problems are canonical combinatorial optimization tasks with wide-ranging applications in logistics, transportation, and supply chain management. However, solving these problems becomes significantly more challen…
Combinatorial OptimizationTraveling Salesman ProblemCollaborative Problem-Solving in an Optimization Game
Dialogue agents that support human users in solving complex tasks have received much attention recently. Many such tasks are NP-hard optimization problems that require careful collaborative exploration of the solution sp…
Traveling Salesman ProblemBandit based Dynamic Candidate Edge Selection in Solving Traveling Salesman Problems
Algorithms designed for routing problems typically rely on high-quality candidate edges to guide their search, aiming to reduce the search space and enhance the search efficiency. However, many existing algorithms, like …
Traveling Salesman ProblemPreference Optimization for Combinatorial Optimization Problems
Reinforcement Learning (RL) has emerged as a powerful tool for neural combinatorial optimization, enabling models to learn heuristics that solve complex problems without requiring expert knowledge. Despite significant pr…
Combinatorial OptimizationReinforcement Learning (RL)Traveling Salesman ProblemPurity Law for Generalizable Neural TSP Solvers
Achieving generalization in neural approaches across different scales and distributions remains a significant challenge for the Traveling Salesman Problem~(TSP). A key obstacle is that neural networks often fail to learn…
Traveling Salesman ProblemThe Iterative Chainlet Partitioning Algorithm for the Traveling Salesman Problem with Drone and Neural Acceleration
This study introduces the Iterative Chainlet Partitioning (ICP) algorithm and its neural acceleration for solving the Traveling Salesman Problem with Drone (TSP-D). The proposed ICP algorithm decomposes a TSP-D solution …
Graph Neural NetworkTraveling Salesman ProblemLarge Language Models as Particle Swarm Optimizers
Optimization problems often require domain-specific expertise to design problem-dependent methodologies. Recently, several approaches have gained attention by integrating large language models (LLMs) into genetic algorit…
Symbolic RegressionTraveling Salesman ProblemAnnealed Mean Field Descent Is Highly Effective for Quadratic Unconstrained Binary Optimization
In recent years, formulating various combinatorial optimization problems as Quadratic Unconstrained Binary Optimization (QUBO) has gained significant attention as a promising approach for efficiently obtaining optimal or…
Combinatorial OptimizationTraveling Salesman ProblemSteiner Traveling Salesman Problem with Quantum Annealing
The Steiner Traveling Salesman Problem (STSP) is a variant of the classical Traveling Salesman Problem. The STSP involves incorporating steiner nodes, which are extra nodes not originally part of the required visit set b…
Traveling Salesman ProblemOptimizing Package Delivery with Quantum Annealers: Addressing Time-Windows and Simultaneous Pickup and Delivery
Recent research at the intersection of quantum computing and routing problems has been highly prolific. Much of this work focuses on classical problems such as the Traveling Salesman Problem and the Vehicle Routing Probl…
Traveling Salesman ProblemTuneNSearch: a hybrid transfer learning and local search approach for solving vehicle routing problems
This paper introduces TuneNSearch, a hybrid transfer learning and local search approach for addressing different variants of vehicle routing problems (VRP). Recently, multi-task learning has gained much attention for sol…
Graph AttentionMulti-Task LearningTransfer LearningTraveling Salesman ProblemBridging Pattern-Aware Complexity with NP-Hard Optimization: A Unifying Framework and Empirical Study
NP hard optimization problems like the Traveling Salesman Problem (TSP) defy efficient solutions in the worst case, yet real-world instances often exhibit exploitable patterns. We propose a novel patternaware complexity …
Meta-LearningTraveling Salesman ProblemNavigating Intelligence: A Survey of Google OR-Tools and Machine Learning for Global Path Planning in Autonomous Vehicles
We offer a new in-depth investigation of global path planning (GPP) for unmanned ground vehicles, an autonomous mining sampling robot named ROMIE. GPP is essential for ROMIE's optimal performance, which is translated int…
Autonomous VehiclesQ-LearningTraveling Salesman ProblemLearning to Reduce Search Space for Generalizable Neural Routing Solver
Constructive neural combinatorial optimization (NCO) has attracted growing research attention due to its ability to solve complex routing problems without relying on handcrafted rules. However, existing NCO methods face …
Combinatorial OptimizationTraveling Salesman ProblemLeveraging Large Language Models to Develop Heuristics for Emerging Optimization Problems
Combinatorial optimization problems often rely on heuristic algorithms to generate efficient solutions. However, the manual design of heuristics is resource-intensive and constrained by the designer's expertise. Recent a…
Combinatorial OptimizationIn-Context LearningTraveling Salesman ProblemSolving the Traveling Salesman Problem via Different Quantum Computing Architectures
We study the application of emerging photonic and quantum computing architectures to solving the Traveling Salesman Problem (TSP), a well-known NP-hard optimization problem. We investigate several approaches: Simulated A…
Traveling Salesman ProblemDestroy and Repair Using Hyper Graphs for Routing
Recent advancements in Neural Combinatorial Optimization (NCO) have shown promise in solving routing problems like the Traveling Salesman Problem (TSP) and Capacitated Vehicle Routing Problem (CVRP) without handcrafted d…
Combinatorial OptimizationTraveling Salesman Problem