Cost-allocation problems for fuzzy agents in a fixed-tree network

Cost-allocation problems in a fixed network are concerned with distributing the costs for use by a group of clients who cooperate in order to reduce such costs. We work only with tree networks and we assume that a minimum cost spanning tree network has already been constructed and now we are interested in the maintenance costs. The classic problem supposes that each agent stays for the entire time in the same node of the network. This paper introduces cost-allocation problems in a fixed-tree network with a set of agents whose activity over the nodes is fuzzy. Agent’s needs to pay for each period of time may differ. Moreover, the agents do not always remain in the same node for each period. We propose the extension of a very well-known solution for these problems: Bird’s rule.Ministerio de Economía y Competitividad MTM2017-83455-PJunta de Andalucía FQM23

Bird's tree allocations revisited

Game Theory;Cost Allocation

Implicit Decomposition for Write-Efficient Connectivity Algorithms

The future of main memory appears to lie in the direction of new technologies that provide strong capacity-to-performance ratios, but have write operations that are much more expensive than reads in terms of latency, bandwidth, and energy. Motivated by this trend, we propose sequential and parallel algorithms to solve graph connectivity problems using significantly fewer writes than conventional algorithms. Our primary algorithmic tool is the construction of an $o(n)$-sized "implicit decomposition" of a bounded-degree graph $G$ on $n$ nodes, which combined with read-only access to $G$ enables fast answers to connectivity and biconnectivity queries on $G$. The construction breaks the linear-write "barrier", resulting in costs that are asymptotically lower than conventional algorithms while adding only a modest cost to querying time. For general non-sparse graphs on $m$ edges, we also provide the first $o(m)$ writes and $O(m)$ operations parallel algorithms for connectivity and biconnectivity. These algorithms provide insight into how applications can efficiently process computations on large graphs in systems with read-write asymmetry

Defining Rules in Cost Spanning Tree Problems Through the Canonical Form

We define the canonical form of a cost spanning tree problem. The canonical form has the property that reducing the cost of any arc, the minimal cost of connecting agents to the source is also reduced. We argue that the canonical form is a relevant concept in this kind of problems and study a rule using it. This rule satisfies much more interesting properties than other rules in the literature. Furthermore we provide two characterizations. Finally, we present several approaches to this rule without using the canonical form.Cost spanning tree, Rules, Canonical form

A non-cooperative approach to the folk rule in minimum cost spanning tree problems

This paper deals with the problem of finding a way to distribute the cost of a minimum cost spanning tree problem between the players. A rule that assigns a payoff to each player provides this distribution. An optimistic point of view is considered to devise a cooperative game. Following this optimistic approach, a sequential game provides this construction to define the action sets of the players. The main result states the existence of a unique cost allocation in subgame perfect equilibria. This cost allocation matches the one suggested by the folk rule.The authors thank the support of the Spanish Ministry of Science, Innovation and Universities, the Spanish Ministry of Economy and Competitiveness, the Spanish Agency of Research, co-funded with FEDER funds, under the projects ECO2016-77200-P, ECO2017-82241-R, ECO2017-87245-R, PID2021-128228NB-I00, Consellería d’Innovación, Universitats, Ciencia i Societat Digital, Generalitat Valenciana [grant number AICO/2021/257], and Xunta de Galicia (ED431B 2019/34)

Initial detailed routing algorithms

In this work, we present a study of the problem of routing in the context of the VLSI physical synthesis flow. We study the fundamental routing algorithms such as maze routing, A*, and Steiner tree-based algorithms, as well as some global routing algorithms, namely FastRoute 4.0 and BoxRouter 2.0. We dissect some of the major state of the art initial detailed routing tools, such as RegularRoute, TritonRoute, SmartDR and Dr.CU 2.0. We also propose an initial detailed routing flow, and present an implementation of the proposed routing flow, with a track assignment technique that models the problem as an instance of the maximum independent weighted set (MWIS) and utilizes integer linear programming (ILP) as a solver. The implementation of the proposed initial detailed routing flow also includes an implementation of multiple-source and multiple-target A* for terminal andnet connection with adjustable rules and weights. Finally, we also present a study of the results obtained by the implementation of the proposed initial detailed routing flow and a comparison with the ISPD 2019 contest winners, considering the ISPD 2019 and benchmark suite and evaluation tools.Neste trabalho, apresentamos um estudo do problema de roteamento no contexto do fluxo de síntese física de circuitos integrados VLSI. Nós estudamos algoritmos de roteamento fundamentais como roteamento de labirinto, A* e baseados em árvores de Steiner, além de alguns algoritmos de roteamento global como FastRoute 4.0 e BoxRouter 2.0. Nós dissecamos alguns dos principais trabalhos de roteamento detalhado inicial do estado da arte, como RegularRoute, TritonRoute, SmartDR e Dr.CU 2.0. Também propomos um fluxo de roteamento detalhado inicial, e apresentamos uma implementação do fluxo de roteametno proposto, com uma técnica de assinalamento de trilhas que modela o problema como uma instância do problema do conjunto independente de peso máximo e usa programação linear inteira como um resolvedor. A implementação do fluxo de rotemaento detalhado inicial proposto também inclui uma implementação de um A* com múltiplas fontes e múltiplos destinos para conexão de terminais e redes, com regras e pesos ajustáveis. Por fim, nós apresentamos um estudo dos resultados obtidos pela implementação do fluxo de roteamento detalhado inicial proposto e comparamos com os vencedores do ISPD 2019 contest considerando a suíte de teste e ferramentas de avaliação do ISPD 2019

Matroid Bandits: Fast Combinatorial Optimization with Learning

A matroid is a notion of independence in combinatorial optimization which is closely related to computational efficiency. In particular, it is well known that the maximum of a constrained modular function can be found greedily if and only if the constraints are associated with a matroid. In this paper, we bring together the ideas of bandits and matroids, and propose a new class of combinatorial bandits, matroid bandits. The objective in these problems is to learn how to maximize a modular function on a matroid. This function is stochastic and initially unknown. We propose a practical algorithm for solving our problem, Optimistic Matroid Maximization (OMM); and prove two upper bounds, gap-dependent and gap-free, on its regret. Both bounds are sublinear in time and at most linear in all other quantities of interest. The gap-dependent upper bound is tight and we prove a matching lower bound on a partition matroid bandit. Finally, we evaluate our method on three real-world problems and show that it is practical