Zobrazeno 1 - 10
of 63
pro vyhledávání: '"Wang, Xinshang"'
Quadratic programming (QP) is the most widely applied category of problems in nonlinear programming. Many applications require real-time/fast solutions, though not necessarily with high precision. Existing methods either involve matrix decomposition
Externí odkaz:
http://arxiv.org/abs/2406.05938
Graph neural networks (GNNs) have been widely used to predict properties and heuristics of mixed-integer linear programs (MILPs) and hence accelerate MILP solvers. This paper investigates the capacity of GNNs to represent strong branching (SB), the m
Externí odkaz:
http://arxiv.org/abs/2402.07099
In this work, we propose a novel optimization model termed "sum-of-minimum" optimization. This model seeks to minimize the sum or average of $N$ objective functions over $k$ parameters, where each objective takes the minimum value of a predefined sub
Externí odkaz:
http://arxiv.org/abs/2402.07070
Mixed-integer linear programming (MILP) stands as a notable NP-hard problem pivotal to numerous crucial industrial applications. The development of effective algorithms, the tuning of solvers, and the training of machine learning models for MILP reso
Externí odkaz:
http://arxiv.org/abs/2310.13261
While Mixed-integer linear programming (MILP) is NP-hard in general, practical MILP has received roughly 100--fold speedup in the past twenty years. Still, many classes of MILPs quickly become unsolvable as their sizes increase, motivating researcher
Externí odkaz:
http://arxiv.org/abs/2210.10759
Learning to optimize is a rapidly growing area that aims to solve optimization problems or improve existing optimization algorithms using machine learning (ML). In particular, the graph neural network (GNN) is considered a suitable ML model for optim
Externí odkaz:
http://arxiv.org/abs/2209.12288
We study the canonical quantity-based network revenue management (NRM) problem where the decision-maker must irrevocably accept or reject each arriving customer request with the goal of maximizing the total revenue given limited resources. The exact
Externí odkaz:
http://arxiv.org/abs/2011.06327
The recent rising popularity of ultra-fast delivery services on retail platforms fuels the increasing use of urban warehouses, whose proximity to customers makes fast deliveries viable. The space limit in urban warehouses poses a problem for the onli
Externí odkaz:
http://arxiv.org/abs/1903.07844
Classically, the time complexity of a first-order method is estimated by its number of gradient computations. In this paper, we study a more refined complexity by taking into account the `lingering' of gradients: once a gradient is computed at $x_k$,
Externí odkaz:
http://arxiv.org/abs/1901.02871
Autor:
Truong, Van-Anh, Wang, Xinshang
The classical Prophet Inequality arises from a fundamental problem in optimal-stopping theory. In this problem, a gambler sees a finite sequence of independent, non-negative random variables. If he stops the sequence at any time, he collects a reward
Externí odkaz:
http://arxiv.org/abs/1901.02552