POPMUSIC for the Travelling Salesman Problem

POPMUSIC— Partial OPtimization Metaheuristic Under Special Intensification Conditions — is a template for tackling large problem instances. This metaheuristic has been shown to be very efficient for various hard combinatorial problems such as p-median, sum of squares clustering, vehicle routing, map labelling and location routing. A key point for treating large Travelling Salesman Problem (TSP) instances is to consider only a subset of edges connecting the cities. The main goal of this article is to present how to build a list of good candidate edges with a complexity lower than quadratic in the context of TSP instances given by a general function. The candidate edges are found with a technique exploiting tour merging and the POPMUSIC metaheuristic. When these candidate edges are provided to a good local search engine, high quality solutions can be found quite efficiently. The method is tested on TSP instances of up to several million cities with different structures (Euclidean uniform, clustered, 2D to 5D, grids, toroidal distances). Numerical results show that solutions of excellent quality can be obtained with an empirical complexity lower than quadratic without exploiting the geometrical properties of the instances

A User’s Guide to Tabu Search

We describe the main features of tabu search, emphasizing a perspective for guiding a user to widerstand basic implementation principles for solving combinatorial or nonlinear problems. We also identify recent developments and extensions that have contributed to increasing the efficiency of the method. One of the useful aspects of tabu search is the ability to adapt a rudimentary prototype implementation to encompass additional model elements, such as new types of constraints and objective functions. Similarly, the method itself can be evolved to varying levels of sophistication. We provide several examples of discrete optimization problems to illustrate the strategic concerns of tabu search, and to show how they may be exploited in various contexts. Our presentation is motivated by the emergence of an extensive literature of computational results, which demonstrates that a well-lWled implementation makes it possible to obtain solutions of high quality for difficult problems, yielding outcomes in some settings that have not been matched by other known techniques

Gaspard2 UML profile documentation

This document describes the current UML profile of Gaspard2. This profile extends the UML semantics to allow the user to describe a SoC (System-on-Chip) in three steps: the application (behavior of the Soc), the hardware architecture, and the association of the application to the hardware architecture. The application is represented following a data flow model, but additional mechanisms permit the usage of control flow on those applications. In addition to those notions, the profile contains a package introducing factorization mechanisms to enable the compact description of massively parallel and repetitive systems

Chase-and-run between adjacent cell populations promotes directional collective migration

Collective cell migration in morphogenesis and cancer progression often involves the coordination of multiple cell types. How reciprocal interactions between adjacent cell populations lead to new emergent behaviours remains unknown. Here we studied the interaction between neural crest (NC) cells, a highly migratory cell population, and placodal cells, an epithelial tissue that contributes to sensory organs. We found that NC cells chase placodal cells by chemotaxis, and placodal cells run when contacted by NC. Chemotaxis to Sdf1 underlies the chase, and repulsion involving PCP and N-cadherin signalling is responsible for the run. This chase-and-run requires the generation of asymmetric forces, which depend on local inhibition of focal adhesions. The cell interactions described here are essential for correct NC migration and for segregation of placodes in vivo and are likely to represent a general mechanism of coordinated migration

Ant Systems

This article describes Ant Systems, a meta-heuristic based on an ant foraging metaphor. The presentation of Ant Systems has been somewhat generalized by adding a "Queen" process in charge of co-ordinating classical "Ant" processes, so that recent Ant Systems can be naturally included while remaining close to the metaphor. To illustrate how Ant Systems are practically implemented, a number of applications to the quadratic assignment problem are reviewed. 1 A model of real ants The metaphor on which Ant Systems are based can be illustrated by observations of ants of the species Linepithema humile [2]. An ant colony nest is isolated, and a food source is provided which is accessible by a bridge composed of two branches of the same length. Although the ants are totally free to choose the left or the right branch of the bridge, it is rapidly observed that almost all ants use a given branch, even if there is no reason to prefer the left or the right one. This phenomenon is explained by the ..