16 papers · ranked by Valyu relevance
Anandha Prakash P, Radha R
This research presents a comprehensive electric vehicle (EV) routing framework designed to address the complex interplay of real-world constraints in EV navigation. The proposed system integrates spectral clustering, fuzzy reinforcement learning, and enhanced pathfinding algorithms to compute optimal routes while…
Guannan Lai, Haoran Hu, Han-Jia Ye
We present RouteJudge, an online pairwise preference evaluation framework for LLM routing systems, with a public platform available at https://routejudge.cn. Different from model-level response evaluation, RouteJudge focuses on router-level decision quality. For each user query, multiple routing strategies…
Chuandong Chen, Dishi Lin, Qinghai Liu, Zhifeng Lin
Redistribution layer ordered routing is a critical problem in fan-out wafer-level chip-scale packaging (WLCSP) design. The traditional integer linear programming (ILP) method is inefficient in dealing with the ordered routing problem of multiple-capacity. Hence, we propose a high-performance ordered routing algorithm…
Ayan Maity, Sudeshna Sarkar
In this paper, we study the vehicle routing problem with a finite time horizon. In this routing problem, the objective is to maximize the number of customer requests served within a finite time horizon. We present a novel routing network embedding module which creates local node embedding vectors and a context-aware…
Peter Baile Chen, Weiyue Li, Roth, Dan + 4 more
AI tasks differ in complexity and are best addressed with different computation strategies (e.g., combinations of models and decoding methods). Hence, an effective routing system that maps tasks to the appropriate strategies is crucial. Most prior methods build the routing framework by training a single model across…
Z. K. Abdurahman Baizal, Soni Fajar Surya Gumilang, Rio Nurtantyana, Rahmat Hendrawan + 1 more
Technological developments in recent years led to the emergence of increasingly sophisticated recommender systems to support multi-day travel itineraries that fall under the Tourist Trip Design Problem (TTDP). Various problem analogies are widely used to solve TTDP, such as Traveling Salesman Problem (TSP), Vehicle…
Di Liu, Mengchi Li, Yushun Lei, Pei Yu + 3 more
In order to address the problem of efficiently distributing to multiple demand points within the city and multiple distribution centers on the urban fringes, this paper considers decision-making issues such as the selection of distribution centers and the planning of delivery routes. With the objective of minimizing…
Joshua Betz, Daniel Herber, Jeffrey Niemann
Route planning for military vehicles is a complex decision-making problem due to the simultaneous influence of environmental trafficability and tactical risks. This paper presents an optimization model that integrates soil trafficability and risk of enemy engagement into a decision-support model for planning activities…
Tomi Suomi, Jalmari Kettunen, Taneli Pusa, Laura L. Elo
Reproducibility is fundamental to reliable scientific discoveries. The reproducibility-optimized test statistic (ROTS) is a robust framework designed to identify reproducible features (e.g. genes or proteins) in high-dimensional differential expression analyses such as transcriptomics and proteomics. This is achieved…
Jingyang Zhao, Mingyu Xiao
The capacitated vehicle routing problem (CVRP) is one of the most extensively studied problems in combinatorial optimization. In this problem, we are given a depot and a set of customers, each with a demand, embedded in a metric space. The objective is to find a set of tours, each starting and ending at the depot…
Bart van Rossum, Rui Chen, Andrea Lodi
We study the fair capacitated vehicle routing problem, in which a fleet of vehicles must serve a set of customers such that the difference between the longest and shortest route, the range, is minimized. A key challenge is that the range objective is non-monotonic: it can be reduced by artificially lengthening routes…
Junqi Huang, Hawraa Abbas Almurieb, T. Nandha Kumar, Haider A. F. Almurib + 1 more
The Traveling Salesman Problem (TSP) continues to attract significant research interest due to its critical role in various applications. This paper introduces a recursive clustering approach that divides cities into a limited number of clusters, each containing up to five cities and its own centroid. Constrained TSP…
Authors not listed
The automated discovery of chemical and catalytic reactions remains a major challenge in computational chemistry, particularly in complex systems where conventional methods struggle to identify optimal searching directions. Here, we propose Loxodynamics, a machine-learning-driven approach for reaction exploration via…
Christopher R. Nolan, Mike E. Le Pelley, Kelly G. Garner
The benefits of routines for daily functioning are widely acknowledged, yet, despite their apparent importance, methods for quantifying routine maintenance and the causes of their disruption remain lacking. Here, we propose a novel means of defining and quantifying routines (transition entropy). Using the transition…
Alexander Krauss, Wen-Dong Li
Powerful new methods and tools drive scientific progress-but how do we actually make such innovations? No theory yet explains how we invent major tools across fields. To address this gap, we examine all nobel-prize-winning method discoveries-that enabled breakthrough findings not possible without them-and we trace…
Authors not listed
Collective variables (CVs) are essential for interpreting and accelerating rare events in molecular simulations. However, their design remains limited by the requirement of differentiability with respect to atomic coordinates. This constraint excludes many powerful structural descriptors that are routinely used for…