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In an emergency situation, the evacuation of a large crowd from a complex building can become slow or even dangerous without a working evacuation plan. The use of rescue guides that lead the crowd out of the building can improve the…

Physics and Society · Physics 2021-08-23 Anton von Schantz , Harri Ehtamo

We investigate online convex optimization in non-stationary environments and choose dynamic regret as the performance measure, defined as the difference between cumulative loss incurred by the online algorithm and that of any feasible…

Machine Learning · Computer Science 2024-04-09 Peng Zhao , Yu-Jie Zhang , Lijun Zhang , Zhi-Hua Zhou

In this paper the minmax (regret) versions of some basic polynomially solvable deterministic network problems are discussed. It is shown that if the number of scenarios is unbounded, then the problems under consideration are not…

Computational Complexity · Computer Science 2008-10-24 Adam Kasperski , Pawel Zielinski

This paper addresses resource allocation problem with a separable objective function under a single linear constraint, formulated as maximizing $\sum_{j=1}^{n}R_j(x_j)$ subject to $\sum_{j=1}^{n}x_j=k$ and $x_j\in\{0,\dots,m\}$. While…

Data Structures and Algorithms · Computer Science 2025-09-10 Song Cao , Taikun Zhu , Kai Jin

A constrained version of the online convex optimization (OCO) problem is considered. With slotted time, for each slot, first an action is chosen. Subsequently the loss function and the constraint violation penalty evaluated at the chosen…

Machine Learning · Computer Science 2023-01-25 Rahul Vaze

We investigate online convex optimization in non-stationary environments and choose the dynamic regret as the performance measure, defined as the difference between cumulative loss incurred by the online algorithm and that of any feasible…

Machine Learning · Computer Science 2020-12-01 Peng Zhao , Yu-Jie Zhang , Lijun Zhang , Zhi-Hua Zhou

In this paper, we broaden the horizon of online convex optimization (OCO), and consider multi-objective OCO, where there are $K$ distinct loss function sequences, and an algorithm has to choose its action at time $t$, before the $K$ loss…

Machine Learning · Computer Science 2026-02-11 Rahul Vaze , Sumiran Mishra

This paper considers the distributed online convex optimization problem with time-varying constraints over a network of agents. This is a sequential decision making problem with two sequences of arbitrarily varying convex loss and…

Optimization and Control · Mathematics 2022-12-29 Xinlei Yi , Xiuxian Li , Tao Yang , Lihua Xie , Tianyou Chai , Karl H. Johansson

Given $n$ points in a circular region $C$ in the plane, we study the problems of moving the $n$ points to its boundary to form a regular $n$-gon such that the maximum (min-max) or the sum (min-sum) of the Euclidean distances traveled by the…

Computational Geometry · Computer Science 2011-07-07 Danny Z. Chen , Xuehou Tan , Haitao Wang , Gangshan Wu

The regret bound of dynamic online learning algorithms is often expressed in terms of the variation in the function sequence ($V_T$) and/or the path-length of the minimizer sequence after $T$ rounds. For strongly convex and smooth…

Machine Learning · Computer Science 2020-08-17 Ting-Jui Chang , Shahin Shahrampour

We give an O(n log^3 n) algorithm that, given an n-node directed planar graph with arc capacities, a set of source nodes, and a set of sink nodes, finds a maximum flow from the sources to the sinks. Previously, the fastest algorithms known…

Discrete Mathematics · Computer Science 2011-05-12 Glencora Borradaile , Philip N. Klein , Shay Mozes , Yahav Nussbaum , Christian Wulff-Nilsen

In this paper we present an O(n log n) algorithm for finding a maximum flow in a directed planar graph, where the vertices are subject to capacity constraints, in addition to the arcs. If the source and the sink are on the same face, then…

Discrete Mathematics · Computer Science 2009-05-05 Haim Kaplan , Yahav Nussbaum

In this paper, we consider the problem of distributed online convex optimization, where a group of agents collaborate to track the global minimizers of a sum of time-varying objective functions in an online manner. Specifically, we propose…

Optimization and Control · Mathematics 2020-10-14 Yan Zhang , Robert J. Ravier , Vahid Tarokh , Michael M. Zavlanos

State-of-the-art emergency navigation approaches are designed to evacuate civilians during a disaster based on real-time decisions using a pre-defined algorithm and live sensory data. Hence, casualties caused by the poor decisions and…

Other Computer Science · Computer Science 2015-01-06 Huibo Bi , Erol Gelenbe

We consider the problem of finding maximum flows in planar graphs with capacities on both vertices and edges and with multiple sources and sinks. We present three algorithms when the capacities are integers. The first algorithm runs in $O(n…

Data Structures and Algorithms · Computer Science 2021-05-26 Yipu Wang

We present a congestion-aware routing solution for indoor evacuation, which produces real-time individual-customized evacuation routes among multiple destinations while keeping tracks of all evacuees' locations. A population density map,…

Human-Computer Interaction · Computer Science 2020-04-28 Zeyu Zhang , Hangxin Liu , Ziyuan Jiao , Yixin Zhu , Song-Chun Zhu

In case of a threat in a public space, the crowd in it should be moved to a shelter or evacuated without delays. Risk management and evacuation planning in public spaces should also take into account uncertainties in the traffic patterns of…

Physics and Society · Physics 2021-03-31 Anton von Schantz , Harri Ehtamo , Simo Hostikka

This paper addresses a version of the single-facility Maximal Covering Location Problem on a network where the demand is: (i) distributed along the edges and (ii) uncertain with only a known interval estimation. To deal with this problem,…

Optimization and Control · Mathematics 2024-09-19 Marta Baldomero-Naranjo , Jörg Kalcsics , Antonio M. Rodríguez-Chía

We consider the classic problem of online convex optimisation. Whereas the notion of static regret is relevant for stationary problems, the notion of switching regret is more appropriate for non-stationary problems. A switching regret is…

Machine Learning · Computer Science 2025-03-07 Stephen Pasteris , Chris Hicks , Vasilios Mavroudis , Mark Herbster

The problem of finding the optimal placement of emergency exits in an indoor environment to facilitate the rapid and orderly evacuation of crowds is addressed in this work. A cellular-automaton model is used to simulate the behavior of…

Neural and Evolutionary Computing · Computer Science 2024-05-29 Carlos Cotta , José E. Gallardo