Decomposition, Reformulation, and Diving in University Course Timetabling

In many real-life optimisation problems, there are multiple interacting components in a solution. For example, different components might specify assignments to different kinds of resource. Often, each component is associated with different sets of soft constraints, and so with different measures of soft constraint violation. The goal is then to minimise a linear combination of such measures. This paper studies an approach to such problems, which can be thought of as multiphase exploitation of multiple objective-/value-restricted submodels. In this approach, only one computationally difficult component of a problem and the associated subset of objectives is considered at first. This produces partial solutions, which define interesting neighbourhoods in the search space of the complete problem. Often, it is possible to pick the initial component so that variable aggregation can be performed at the first stage, and the neighbourhoods to be explored next are guaranteed to contain feasible solutions. Using integer programming, it is then easy to implement heuristics producing solutions with bounds on their quality. Our study is performed on a university course timetabling problem used in the 2007 International Timetabling Competition, also known as the Udine Course Timetabling Problem. In the proposed heuristic, an objective-restricted neighbourhood generator produces assignments of periods to events, with decreasing numbers of violations of two period-related soft constraints. Those are relaxed into assignments of events to days, which define neighbourhoods that are easier to search with respect to all four soft constraints. Integer programming formulations for all subproblems are given and evaluated using ILOG CPLEX 11. The wider applicability of this approach is analysed and discussed.Comment: 45 pages, 7 figures. Improved typesetting of figures and table

Bargaining and Influence in Conflict Situations

[Excerpt] This chapter examines bargaining as an influence process through which actors attempt to resolve a social conflict. Conflict occurs when two or more interdependent actors have incompatible preferences and perceive or anticipate resistance from each other (Blalock 1989; Kriesberg 1982). Bargaining is a basic form of goal-directed action that involves both intentions to influence and efforts by each actor to carry out these intentions. Tactics are verbal and/or nonverbal actions designed to maneuver oneself into a favorable position vis-a-vis another or to reach some accommodation. Our treatment of bargaining subsumes the concept of negotiation (see Morley and Stephenson 1977). This chapter is organized around a conceptual framework that distinguishes basic types of bargaining contexts. We begin by introducing the framework and then present an overview of and analyze theoretical and empirical work on each type of bargaining context

Incremental Grid-like Layout Using Soft and Hard Constraints

We explore various techniques to incorporate grid-like layout conventions into a force-directed, constraint-based graph layout framework. In doing so we are able to provide high-quality layout---with predominantly axis-aligned edges---that is more flexible than previous grid-like layout methods and which can capture layout conventions in notations such as SBGN (Systems Biology Graphical Notation). Furthermore, the layout is easily able to respect user-defined constraints and adapt to interaction in online systems and diagram editors such as Dunnart.Comment: Accepted to Graph Drawing 201

Cluster counting: The Hoshen-Kopelman algorithm vs. spanning tree approaches

Two basic approaches to the cluster counting task in the percolation and related models are discussed. The Hoshen-Kopelman multiple labeling technique for cluster statistics is redescribed. Modifications for random and aperiodic lattices are sketched as well as some parallelised versions of the algorithm are mentioned. The graph-theoretical basis for the spanning tree approaches is given by describing the "breadth-first search" and "depth-first search" procedures. Examples are given for extracting the elastic and geometric "backbone" of a percolation cluster. An implementation of the "pebble game" algorithm using a depth-first search method is also described.Comment: LaTeX, uses ijmpc1.sty(included), 18 pages, 3 figures, submitted to Intern. J. of Modern Physics

India as a Foreign Policy Actor – Normative Redux. CEPS Working Document No. 285, February 2008

This paper analyses India’s behaviour as a foreign policy actor by looking at India’s changing relations over the past decade with the EU, US, China, Japan, Myanmar, Pakistan, Nepal and, in a historical departure, the former princely state of Sikkim. It argues that though India has almost always been a normative actor, Indian foreign policy is today transiting from abstract, and frequently ‘unrealpolitik,’ views of what constitutes normative behaviour. India’s ‘Look East’ policy has been the cornerstone of this transition, indicating that economic growth, maritime capability and peace and stability in its neighbourhood are key goals of India’s present behaviour as a normative foreign policy actor

Combining Relational Algebra, SQL, Constraint Modelling, and Local Search

The goal of this paper is to provide a strong integration between constraint modelling and relational DBMSs. To this end we propose extensions of standard query languages such as relational algebra and SQL, by adding constraint modelling capabilities to them. In particular, we propose non-deterministic extensions of both languages, which are specially suited for combinatorial problems. Non-determinism is introduced by means of a guessing operator, which declares a set of relations to have an arbitrary extension. This new operator results in languages with higher expressive power, able to express all problems in the complexity class NP. Some syntactical restrictions which make data complexity polynomial are shown. The effectiveness of both extensions is demonstrated by means of several examples. The current implementation, written in Java using local search techniques, is described. To appear in Theory and Practice of Logic Programming (TPLP)Comment: 30 pages, 5 figure