Polynomial Time Approximation Scheme for the Minimum-weight k-Size Cycle Cover Problem in Euclidean space of an arbitrary fixed dimension

We study the Min-k-SCCP on the partition of a complete weighted digraph by k vertex-disjoint cycles of minimum total weight. This problem is the generalization of the well-known traveling salesman problem (TSP) and the special case of the classical vehicle routing problem (VRP). It is known that the problem Min-k-SCCP is strongly NP-hard and remains intractable even in the geometric statement. For the Euclidean Min-k-SCCP in Rd, we construct a polynomial-time approximation scheme, which generalizes the approach proposed earlier for the planar Min-2-SCCP. For any fixed c > 1, the scheme finds a (1 + 1/c)-approximate solution in time of O(nd+1(k log n)(O (√dc))d-1 2k). © 201

A concise guide to existing and emerging vehicle routing problem variants

Vehicle routing problems have been the focus of extensive research over the past sixty years, driven by their economic importance and their theoretical interest. The diversity of applications has motivated the study of a myriad of problem variants with different attributes. In this article, we provide a concise overview of existing and emerging problem variants. Models are typically refined along three lines: considering more relevant objectives and performance metrics, integrating vehicle routing evaluations with other tactical decisions, and capturing fine-grained yet essential aspects of modern supply chains. We organize the main problem attributes within this structured framework. We discuss recent research directions and pinpoint current shortcomings, recent successes, and emerging challenges

Matheuristics: using mathematics for heuristic design

Matheuristics are heuristic algorithms based on mathematical tools such as the ones provided by mathematical programming, that are structurally general enough to be applied to different problems with little adaptations to their abstract structure. The result can be metaheuristic hybrids having components derived from the mathematical model of the problems of interest, but the mathematical techniques themselves can define general heuristic solution frameworks. In this paper, we focus our attention on mathematical programming and its contributions to developing effective heuristics. We briefly describe the mathematical tools available and then some matheuristic approaches, reporting some representative examples from the literature. We also take the opportunity to provide some ideas for possible future development

Modelo matemático para seleção de rotas de patrulhamento escolar: o caso da patrulha escolar de Ponta Grossa

Studies have shown that school violence produces harmful effects on victims and society alike. Police patrols have proved to me the most effective among the main forms of preventing school violence. School police patrols take place using squad cars that serve a network of schools and consist of placing vehicles at network schools for a given period of time (routine patrol). Nevertheless, during routine patrol police vehicles must immediately answer emergency calls at network schools that are not being patrolled at that moment (emergency patrolling). This work proposes a method based on mathematical models to assist the school patrol program in defining the routes for routine patrol and emergency routes. The approach used to solve the problem consisted of graph algorithms. Routine patrol was treated as a model of the Traveling Salesman Problem, and was solved using the Nearest Neighbor Heuristic and Tabu Search metaheuristic. The emergency situation was modeled using the Shortest Path Problem, and emergency routes were determined through the Floyd-Warshall algorithm. A case study was used to demonstrate the application of the method. Results show that the proposed method is effective to treat the problem of route selection for school patrols in cities with shortcomings in technological resources.CAPESEstudos mostram que a violência nas escolas resulta em consequências prejudiciais para as vítimas e para a sociedade. Entre os principais meios de prevenção da violência escolar tem-se o patrulhamento policial como o mais efetivo. O patrulhamento policial escolar é realizado por viaturas policiais que atendem a uma rede de escolas e consiste na manutenção das viaturas em cada escola da rede por um determinado período de tempo (patrulhamento de rotina). Contudo, durante o patrulhamento de rotina, as viaturas devem prestar atendimento imediato a chamadas de emergência em escolas da rede que não estejam sendo patrulhadas naquele momento (patrulhamento emergencial). O presente trabalho propõe um método baseado em modelos matemáticos para auxiliar o programa de patrulha escolar na definição das rotas de patrulhamento de rotina e rotas emergenciais. A abordagem aplicada para resolver o problema foi a de algoritmos de grafos. O patrulhamento de rotina foi por meio do Problema do caixeiro viajante e solucionado por meio da heurística do vizinho mais próximo e da meta-heurística de Busca tabu. A situação de emergência foi modelada utilizando o Caminho mais curto e as rotas emergenciais foram determinadas por meio do algoritmo de Floyd-Warshall. Um estudo de caso em uma rede de escolas foi utilizado para demonstrar a utilização do método. Os resultados mostram que o método proposto é efetivo para tratar o problema de seleção de rotas de patrulhamento escolar em cidades com restrições de recursos tecnológicos

Model-Based Heuristics for Combinatorial Optimization

Many problems arising in several and different areas of human knowledge share the characteristic of being intractable in real cases. The relevance of the solution of these problems, linked to their domain of action, has given birth to many frameworks of algorithms for solving them. Traditional solution paradigms are represented by exact and heuristic algorithms. In order to overcome limitations of both approaches and obtain better performances, tailored combinations of exact and heuristic methods have been studied, giving birth to a new paradigm for solving hard combinatorial optimization problems, constituted by model-based metaheuristics. In the present thesis, we deepen the issue of model-based metaheuristics, and present some methods, belonging to this class, applied to the solution of combinatorial optimization problems