Valid inequalities for a single constrained 0-1 MIP set intersected with a conflict graph

In this paper a mixed integer set resulting from the intersection of a single constrained mixed 0–1 set with the vertex packing set is investigated. This set arises as a subproblem of more general mixed integer problems such as inventory routing and facility location problems. Families of strong valid inequalities that take into account the structure of the simple mixed integer set and that of the vertex packing set simultaneously are introduced. In particular, the well-known mixed integer rounding inequality is generalized to the case where incompatibilities between binary variables are present. Exact and heuristic algorithms are designed to solve the separation problems associated to the proposed valid inequalities. Preliminary computational experiments show that these inequalities can be useful to reduce the integrality gaps and to solve integer programming problems

Relaxations and Cutting Planes for Linear Programs with Complementarity Constraints

We study relaxations for linear programs with complementarity constraints, especially instances whose complementary pairs of variables are not independent. Our formulation is based on identifying vertex covers of the conflict graph of the instance and generalizes the extended reformulation-linearization technique of Nguyen, Richard, and Tawarmalani to instances with general complementarity conditions between variables. We demonstrate how to obtain strong cutting planes for our formulation from both the stable set polytope and the boolean quadric polytope associated with a complete bipartite graph. Through an extensive computational study for three types of practical problems, we assess the performance of our proposed linear relaxation and new cutting-planes in terms of the optimality gap closed

Algorithms for Cell Layout

Cell layout is a critical step in the design process of computer chips. A cell is a logic function or storage element implemented in CMOS technology by transistors connected with wires. As each cell is used many times on a chip, improvements of a single cell layout can have a large effect on the overall chip performance. In the past years increasing difficulty to manufacture small feature sizes has lead to growing complexity of design rules. Producing cell layouts which are compliant with design rules and at the same time optimized w.r.t. layout size has become a difficult task for human experts. In this thesis we present BonnCell, a cell layout generator which is able to fully automatically produce design rule compliant layouts. It is able to guarantee area minimality of its layouts for small and medium sized cells. For large cells it uses a heuristic which produces layouts with a significant area reduction compared to those created manually. The routing problem is based on the Vertex Disjoint Steiner Tree Packing Problem with a large number of additional design rules. In Chapter 4 we present the routing algorithm which is based on a mixed integer programming (MIP) formulation that guarantees compliance with all design rules. The algorithm can also handle instances in which only part of the transistors are placed to check whether this partial placement can be extended to a routable placement of all transistors. Chapter 5 contains the transistor placement algorithm. Based on a branch and bound approach, it places transistors in turn and achieves efficiency by pruning parts of the search tree which do not contain optimum solutions. One major contribution of this thesis is that BonnCell only outputs routable placements. Simply checking the routability for each full placement in the search tree is too slow in practice, therefore several speedup strategies are applied. Some cells are too large to be solved by a single call of the placement algorithm. In Chapter 7 we describe how these cells are split up into smaller subcells which are placed and routed individually and subsequently merged into a placement and routing of the original cell. Two approaches for dividing the original cell into subcells are presented, one based on estimating the subcell area and the other based on solving the Min Cut Linear Arrangement Problem. BonnCell has enabled our cooperation partner IBM to drastically improve their cell design and layout process. In particular, a team of human experts needed several weeks to find a layout for their largest cell, consisting of 128 transistors. BonnCell processed this cell without manual intervention in 3 days and its layout uses 15% less area than the layout found by the human experts

Robust optimization models with mixed-integer uncertainty sets

In many real-world decision-making problems, some parameters are uncertain and decision-makers have to solve optimization models under uncertainty. In this study, we address two specific classes of problems with uncertain parameters and we are interested in solutions that are robust under any realization of uncertainty. The first one is a class of minimum-cost flow problems where the arcs are subject to multiple ripple-effect disruptions that increase their usage cost. The locations of the disruptions' epicenters are uncertain, and the decision-maker seeks a flow that minimizes cost assuming the worst-case realization of the disruptions. We evaluate the damage to each arc using different methods in which the arcs’ costs post-disruptions are represented with a mixed-integer feasible region. In the second class, we propose a novel problem that considers a decision-maker (a government agency or a public-private consortium) who seeks to efficiently allocate resources in retrofitting and recovery strategies to minimize social vulnerability under an uncertain tornado. As tornado paths cannot be forecast reliably, we model the problem using a two-stage robust optimization problem with a mixed-integer nonlinear uncertainty set that represents the tornado damage.In this study, our primary objective is to develop a mathematical and algorithmic framework for modeling and solving these specific problems. To accomplish this goal, we utilize robust optimization to formulate these problems; develop decomposition algorithms inspired by methods of mixed-integer optimization; and exploit the geometrical characteristics of the uncertainty sets to enhance the formulations and algorithms. We test our proposed approaches over real datasets and synthetic instances. The numerical experiments show that our methods provide sound decision-making strategies under uncertainty and achieve orders of magnitude improvements in computational times over standard approaches from the literature

Proceedings of the XIII Global Optimization Workshop: GOW'16

[Excerpt] Preface: Past Global Optimization Workshop shave been held in Sopron (1985 and 1990), Szeged (WGO, 1995), Florence (GO’99, 1999), Hanmer Springs (Let’s GO, 2001), Santorini (Frontiers in GO, 2003), San José (Go’05, 2005), Mykonos (AGO’07, 2007), Skukuza (SAGO’08, 2008), Toulouse (TOGO’10, 2010), Natal (NAGO’12, 2012) and Málaga (MAGO’14, 2014) with the aim of stimulating discussion between senior and junior researchers on the topic of Global Optimization. In 2016, the XIII Global Optimization Workshop (GOW’16) takes place in Braga and is organized by three researchers from the University of Minho. Two of them belong to the Systems Engineering and Operational Research Group from the Algoritmi Research Centre and the other to the Statistics, Applied Probability and Operational Research Group from the Centre of Mathematics. The event received more than 50 submissions from 15 countries from Europe, South America and North America. We want to express our gratitude to the invited speaker Panos Pardalos for accepting the invitation and sharing his expertise, helping us to meet the workshop objectives. GOW’16 would not have been possible without the valuable contribution from the authors and the International Scientific Committee members. We thank you all. This proceedings book intends to present an overview of the topics that will be addressed in the workshop with the goal of contributing to interesting and fruitful discussions between the authors and participants. After the event, high quality papers can be submitted to a special issue of the Journal of Global Optimization dedicated to the workshop. [...

Abstracts for the twentyfirst European workshop on Computational geometry, Technische Universiteit Eindhoven, The Netherlands, March 9-11, 2005

This volume contains abstracts of the papers presented at the 21st European Workshop on Computational Geometry, held at TU Eindhoven (the Netherlands) on March 9–11, 2005. There were 53 papers presented at the Workshop, covering a wide range of topics. This record number shows that the field of computational geometry is very much alive in Europe. We wish to thank all the authors who submitted papers and presented their work at the workshop. We believe that this has lead to a collection of very interesting abstracts that are both enjoyable and informative for the reader. Finally, we are grateful to TU Eindhoven for their support in organizing the workshop and to the Netherlands Organisation for Scientific Research (NWO) for sponsoring the workshop

Visualization Algorithms for Maps and Diagrams

One of the most common visualization tools used by mankind are maps or diagrams. In this thesis we explore new algorithms for visualizing maps (road and argument maps). A map without any textual information or pictograms is often without use so we research also further into the field of labeling maps. In particular we consider the new challenges posed by interactive maps offered by mobile devices. We discuss new algorithmic approaches and experimentally evaluate them

Models and advanced optimization algorithms for the integrated management of logistics operations

Tese de Doutoramento em Engenharia Industrial e de Sistemas.In this thesis, we propose a set of algorithms regarding real combinatorial optimization problems in the context of transportation of goods. These problems consist in the combination of the vehicle routing problem with the two-dimensional bin-packing problem, which is also known as the vehicle routing problem with two-dimensional loading constraints. We also analyzed two related problems, namely the elementary shortest path and the vehicle routing problem with mixed linehauls and backhauls. In both problems, two-dimensional loading constraints are explicitly considered. Two column generation based approaches are proposed for the vehicle routing problem with two-dimensional constraints. The rst one relies on a branch-and-price algorithm with di erent branching schemes. A family of dual valid inequalities is also de ned, aiming to accelerate the convergence of the algorithm. The second approach is based on a set of di erent heuristics strategies, which are applied to the reformulated model. The elementary shortest path problem with two-dimensional constraints is addressed due to its importance in solving the subproblem of the column generation algorithms. To the best of our knowledge, we contribute with the rst approach for this problem, through di erent constructive strategies to achieve feasible solutions, and a variable neighborhood search algorithm in order to search for improved solutions. In what concerns the vehicle routing problem with mixed linehaul and backhauls and two-dimensional loading constraints, di erent variable neighborhood search algorithms are proposed. These algorithms explored various neighborhood structures, being some of those developed based on the features of the problem. All the proposed methods were implemented and experimentally tested. An exhaustive set of computational tests was conducted, using, for this purpose, a large group of benchmark instances. In some cases, a large set of benchmark instances was adapted in order asses the quality of the proposed models. All the obtained results are presented and discussed.Nesta tese, propomos um conjunto de algoritmos sobre problemas reais de otimiza c~ao combinat oria no contexto do transporte de bens. Estes problemas consistem na combina c~ao do problema de planeamento de rotas de ve culos com o problema de empacotamento bidimensional, que tamb em e conhecido como o problema de planeamento de rotas de ve culos com restri c~oes de carregamento bidimensional. Analisamos tamb em dois problemas relacionados, nomeadamente o problema de caminho mais curto e o problema de planeamento de rotas ve culos com entregas e recolhas indiferenciadas. Em ambos os problemas, s~ao explicitamente consideradas restri c~oes de carregamento bidimensional. Duas abordagens baseadas em gera c~ao de colunas s~ao propostas para o problema de planeamento de rotas de ve culos com restri c~oes de carregamento bidimensional. O primeiro baseia-se num algoritmo de parti c~ao e gera c~ao de colunas com diferentes estrat egias de parti c~ao. Uma fam lia de desigualdades duais v alidas e tamb em apresentada, com o objetivo de acelerar a converg^encia do algoritmo. A segunda abordagem baseia-se num conjunto de diferentes estrat egias heur sticas, que s~ao aplicadas ao modelo reformulado. O problema do caminho mais curto com restri c~oes de carregamento bidimensional e abordado devido a sua import^ancia na resolu c~ao do subproblema dos aos algoritmos de gera c~ao de colunas. De acordo com o nosso conhecimento, contribu mos com a primeira abordagem para este problema, atrav es de diferentes estrat egias construtivas para obter solu c~oes v alidas, e um algoritmo de pesquisa em vizinhan ca vari avel, com o objetivo de encontrar solu c~oes de melhor qualidade. No que concerne ao problema de planeamento de rotas de ve culos com entregas e recolhas indiferenciadas, diferentes algoritmos de pesquisa em vizinhan ca vari avel s~ao propostos. Estes algoritmos exploram v arias estruturas de vizinhan ca, sendo algumas destas desenvolvidas com base nas caracter sticas do problema. Todos os m etodos propostos foram implementados e testados experimentalmente. Um extenso conjunto de testes computacionais foi efetuado, utilizando um grande grupo de inst^ancias descritas na literatura. Em alguns casos, um grande conjunto de inst^ancias descritas na literatura foi adaptado com o objetivo de avaliar a qualidade dos m etodos propostos