Search Trajectory Networks Applied to the Cyclic Bandwidth Sum Problem

Search trajectory networks (STNs) were proposed as a tool to analyze the behavior of metaheuristics in relation to their exploration ability and the search space regions they traverse. The technique derives from the study of fitness landscapes using local optima networks (LONs). STNs are related to LONs in that both are built as graphs, modelling the transitions among solutions or group of solutions in the search space. The key difference is that STN nodes can represent solutions or groups of solutions that are not necessarily locally optimal. This work presents an STN-based study for a particular combinatorial optimization problem, the cyclic bandwidth sum minimization. STNs were employed to analyze the two leading algorithms for this problem: a memetic algorithm and a hyperheuristic memetic algorithm. We also propose a novel grouping method for STNs that can be generally applied to both continuous and combinatorial spaces

Internet of Things in urban waste collection

Nowadays, the waste collection management has an important role in urban areas. This paper faces this issue and proposes the application of a metaheuristic for the optimization of a weekly schedule and routing of the waste collection activities in an urban area. Differently to several contributions in literature, fixed periodic routes are not imposed. The results significantly improve the performance of the company involved, both in terms of resources used and costs saving

Simplified methods for the minimization of open stacks problem.

Este trabalho apresenta dois m?todos para a solu??o do Problema de Minimiza??o de Pilhas Abertas (ou MOSP, de Minimization of Open Stacks Problem), um problema de sequenciamento de padr?es oriundo do contexto de produ??o de pe?as, cuja aplica??o industrial ? direta. O primeiro ? relativo a uma heur?stica baseada em teoria de grafos e crit?rios gulosos, enquanto o segundo ? relativo a um m?todo de programa??o din?mica. Os resultados do experimento realizado comprovam a efic?cia das simplifica??es propostas quando comparadas com os m?todos da literatura.This paper presents two methods for solving the minimization of open stack problem (MOSP), a pattern sequencing problem found in production systems with direct industrial application. The first method refers to a heuristic based on graph theory and greedy criteria, while the second refers to the dynamic programming method. The results show the effectiveness of the proposed simplifications compared to the methods reported in the literature

NASA SERC 1990 Symposium on VLSI Design

This document contains papers presented at the first annual NASA Symposium on VLSI Design. NASA's involvement in this event demonstrates a need for research and development in high performance computing. High performance computing addresses problems faced by the scientific and industrial communities. High performance computing is needed in: (1) real-time manipulation of large data sets; (2) advanced systems control of spacecraft; (3) digital data transmission, error correction, and image compression; and (4) expert system control of spacecraft. Clearly, a valuable technology in meeting these needs is Very Large Scale Integration (VLSI). This conference addresses the following issues in VLSI design: (1) system architectures; (2) electronics; (3) algorithms; and (4) CAD tools

LIPIcs, Volume 274, ESA 2023, Complete Volume

LIPIcs, Volume 274, ESA 2023, Complete Volum

Component-based synthesis of motion planning algorithms

Combinatory Logic Synthesis generates data or runnable programs according to formal type specifications. Synthesis results are composed based on a user-specified repository of components, which brings several advantages for representing spaces of high variability. This work suggests strategies to manage the resulting variations by proposing a domain-specific brute-force search and a machine learning-based optimization procedure. The brute-force search involves the iterative generation and evaluation of machining strategies. In contrast, machine learning optimization uses statistical models to enable the exploration of the design space. The approaches involve synthesizing programs and meta-programs that manipulate, run, and evaluate programs. The methodologies are applied to the domain of motion planning algorithms, and they include the configuration of programs belonging to different algorithmic families. The study of the domain led to the identification of variability points and possible variations. Proof-of-concept repositories represent these variability points and incorporate them into their semantic structure. The selected algorithmic families involve specific computation steps or data structures, and corresponding software components represent possible variations. Experimental results demonstrate that CLS enables synthesis-driven domain-specific optimization procedures to solve complex problems by exploring spaces of high variability.Combinatory Logic Synthesis (CLS) generiert Daten oder lauffähige Programme anhand von formalen Typspezifikationen. Die Ergebnisse der Synthese werden auf Basis eines benutzerdefinierten Repositories von Komponenten zusammengestellt, was diverse Vorteile für die Beschreibung von Räumen mit hoher Variabilität mit sich bringt. Diese Arbeit stellt Strategien für den Umgang mit den resultierenden Variationen vor, indem eine domänen-spezifische Brute-Force Suche und ein maschinelles Lernverfahren für die Untersuchung eines Optimierungsproblems aufgezeigt werden. Die Brute-Force Suche besteht aus der iterativen Generierung und Evaluation von Frässtrategien. Im Gegensatz dazu nutzt der Optimierungsansatz statistische Modelle zur Erkundung des Entwurfsraums. Beide Ansätze synthetisieren Programme und Metaprogramme, welche Programme bearbeiten, ausführen und evaluieren. Diese Methoden werden auf die Domäne der Bewegungsplanungsalgorithmen angewendet und sie beinhalten die Konfiguration von Programmen, welche zu unterschiedlichen algorithmischen Familien gehören. Die Untersuchung der Domäne führte zur Identifizierung der Variabilitätspunkte und der möglichen Variationen. Entsprechende Proof of Concept Implementierungen in Form von Repositories repräsentieren jene Variabilitätspunkte und beziehen diese in ihre semantische Struktur ein. Die gewählten algorithmischen Familien sehen bestimmte Berechnungsschritte oder Datenstrukturen vor, und entsprechende Software Komponenten stellen mögliche Variationen dar. Versuchsergebnisse belegen, dass CLS synthese-getriebene domänenspezifische Optimierungsverfahren ermöglicht, welche komplexe Probleme durch die Exploration von Räumen hoher Variabilität lösen

Métodos y Algoritmos para resolver problemas de Corte unidimensional en entronos realistas. Aplicación a una empresa del sector Siderúrgico

La presente tesis doctoral aborda el análisis y modelización de los problemas de programación en el corte de perfiles estructurales de acero, así como la propuesta de diferentes metodologías y algoritmos basados en técnicas heurísticas que permiten resolverlos de manera óptima. En concreto se profundiza en los siguientes temas: - Se estudia la problemática concreta en el corte de vigas estructurales en una empresa de transformados metalúrgicos. Dicho estudio motiva y justifica todo el trabajo posterior, a la vez que proporciona un contexto concreto en el que aplicar de forma práctica los resultados obtenidos con los algoritmos desarrollados. - Se modeliza matemáticamente el Problema del Corte de vigas a partir de perfiles estructurales. - Se presenta una metodología que resuelve de manera eficiente, mediante el uso de patrones, el Problema del Corte para satisfacer la demanda de vigas en un periodo concreto. A tal efecto se desarrolla: un primer algoritmo genético que genera patrones de corte idóneos (fase 1); un segundo algoritmo genético que determina las frecuencias de uso de cada patrón para minimizar tanto el desperdicio como la sobreproducción (fase 2); y cuatro algoritmos adicionales que mejoran la solución obtenida en la fase anterior (fase 3). - A fin de evaluar la metodología propuesta, se desarrolla un generador de problemas que a partir de unos parámetros de instancia obtiene distintos problemas de test. - Se propone otro algoritmo genético para resolver el Problema multiobjetivo de Secuenciación de Patrones optimizando dos objetivos: minimizar las necesidades de espacio para el apilamiento de pedidos en curso y minimizar la extensión temporal requerida para procesar los pedidos. - Finalmente se propone una metodología para la resolución del Problema Global de Corte y Secuenciación.Gracia Calandin, CP. (2010). Métodos y Algoritmos para resolver problemas de Corte unidimensional en entronos realistas. Aplicación a una empresa del sector Siderúrgico [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/7530Palanci