The Firefighter Problem: A Structural Analysis

We consider the complexity of the firefighter problem where b>=1 firefighters are available at each time step. This problem is proved NP-complete even on trees of degree at most three and budget one (Finbow et al.,2007) and on trees of bounded degree b+3 for any fixed budget b>=2 (Bazgan et al.,2012). In this paper, we provide further insight into the complexity landscape of the problem by showing that the pathwidth and the maximum degree of the input graph govern its complexity. More precisely, we first prove that the problem is NP-complete even on trees of pathwidth at most three for any fixed budget b>=1. We then show that the problem turns out to be fixed parameter-tractable with respect to the combined parameter "pathwidth" and "maximum degree" of the input graph

Spread and defend infection in graphs

The spread of an infection, a contagion, meme, emotion, message and various other spreadable objects have been discussed in several works. Burning and firefighting have been discussed in particular on static graphs. Graph burning simulates the notion of the spread of "fire" throughout a graph (plus, one unburned node burned at each time-step); graph firefighting simulates the defending of nodes by placing firefighters on the nodes which have not been already burned while the fire is being spread (started by only a single fire source). This article studies a combination of firefighting and burning on a graph class which is a variation (generalization) of temporal graphs. Nodes can be infected from "outside" a network. We present a notion of both upgrading (of unburned nodes, similar to firefighting) and repairing (of infected nodes). The nodes which are burned, firefighted, or repaired are chosen probabilistically. So a variable amount of nodes are allowed to be infected, upgraded and repaired in each time step. In the model presented in this article, both burning and firefighting proceed concurrently, we introduce such a system to enable the community to study the notion of spread of an infection and the notion of upgrade/repair against each other. The graph class that we study (on which, these processes are simulated) is a variation of temporal graph class in which at each time-step, probabilistically, a communication takes place (iff an edge exists in that time step). In addition, a node can be "worn out" and thus can be removed from the network, and a new healthy node can be added to the network as well. This class of graphs enables systems with high complexity to be able to be simulated and studied

A computational study of the Firefighter Problem on graphs

Orientadores: Cid Carvalho de Souza, Pedro Jussieu de RezendeDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: O Problema do Brigadista em Grafos (FFP do inglês The Firefighter Problem é um modelo determinístico e em tempo discreto para simular a propagação e contenção de incêndios em grafos. Ele pode ser descrito da seguinte forma. Na entrada, é dado um inteiro D representando a quantidade de brigadistas disponíveis, um grafo não direcionado e não ponderado G = (V,E) e um subconjunto de vértices B de V, os focos de incêndio. Então, inicia-se nos elementos de B um processo iterativo de propagação e contenção de fogo através dos vértices de G, em rodadas discretas, o qual termina quando não existem mais vértices que possam ser queimados, ou seja, quando o fogo está contido. O objetivo ao resolver o FFP é maximizar o número de vértices não queimados quando o fogo é contido, com a restrição de que no máximo D vértices podem ser protegidos contra o fogo por rodada. Aplicações práticas do FFP, além da obtenção de estratégias para minimização de danos causados por incêndios, podem ser encontradas em áreas como controle de doenças e segurança em redes. O FFP é NP-difícil e métodos heurísticos para lidar com o problema foram relatados previamente na literatura. Nessa dissertação, primeiramente, apresentamos melhorias feitas na primeira formulação PLI proposta para o FFP através de técnicas de preprocessamento e agregação de restrições. Em seguida, descrevemos novas heurísticas gulosas e introduzimos uma nova matheurística para o FFP, uma abordagem que se baseia na interoperação entre meta-heurísticas e programação matemática. Experimentos foram conduzidos em um benchmark público tanto para configuração de parâmetros quanto para análise de desempenho, através de comparação dos resultados obtidos com aqueles publicados anteriormente. Com respeito às modificações no modelo PLI, um speedup de aproximadamente 2 em média foi alcançado. Observamos que as modificações feitas podem levar a geração de soluções infactíveis, mas conseguimos demonstrar que é possível tornar tais soluções factíveis em tempo polinomial. Em referência às heurísticas, essas foram executadas seguindo uma metodologia para construir uma solução na qual escolhas gulosas aleatorizadas são realizadas para selecionar quais vértices serão defendidos, de acordo com conceitos introduzidos na meta-heurística GRASP. Comparando essas heurísticas com as que foram propostas por trabalhos anteriores, observamos que duas das nossas estão entre as cinco melhores na maioria dos casos. Com relação à matheurística, através de uma análise estatística rigorosa, verificamos que existe diferença estatisticamente significativa entre nossa estratégia e as demais, ao mesmo tempo que nossa matheurística conseguiu resultados melhores na maioria das instânciasAbstract: The firefighter problem (FFP) is a deterministic discrete-time model for the spread and containment of fire on a graph. Such problem is described as follows. As its inputs, there is an integer D representing the number of available firefighters, an undirected and unweighted graph G=(V, E) and a subset of vertices B of V, the fire outbreaks. Then, an iterative process of fire propagation and containment through the vertices of G is started at the ones from B. This process ends when there are no more vertices to be burnt, that is, the fire is contained. The goal when solving the FFP is to maximize the number of vertices that are not burned when the fire is contained, with the constraint that at most D vertices can be protected against the fire per iteration. Practical applications of the FFP, besides obtaining strategies to minimize the damage caused by fire, can be found in areas such as disease control and network security. The FFP is NP-hard and heuristic methods to tackle the problem were proposed earlier in the literature. In this dissertation, firstly we present modifications made on the first ILP model proposed to the FFP through techniques of preprocessing and constraint aggregation. Moreover, we describe new greedy heuristics and also we introduce a novel matheuristic to the FFP, an approach based on the interoperation between metaheuristics and mathematical programming. A series of computational experiments were conducted on a public benchmark both for parameter tuning and to compare our results with those obtained previously. In respect to the modifications on the ILP model, a speedup of 2 in average was obtained. While constraint aggregation can lead to infeasible solutions, we prove that the latter can be converted to feasible ones in linear time. Regarding the heuristics, they were executed following a methodology to construct a solution in which greedy randomized choices are made to select which vertices should be defended, according to concepts introduced by the GRASP metaheuristic. Comparing these heuristics with the ones proposed by previous works, we observe that two of ours are between the five best ones in general. In relation to the matheuristic, through rigorous statistical analysis, we were able to verify that there is a statistically significant difference between our strategy and the remaining ones, while our matheuristic had better results on the majority of the instancesMestradoCiência da ComputaçãoMestre em Ciência da Computação133728/2016-1CNP