A comparative approach of ant colony system and mathematical programming for task scheduling in a mineral analysis laboratory

This paper considers the problem of scheduling a given set of samples in a mineral laboratory, located in Barranquilla Colombia. Taking into account the natural complexity of the process and the large amount of variables involved, this problem is considered as NP-hard in strong sense. Therefore, it is possible to find an optimal solution in a reasonable computational time only for small instances, which in general, does not reflect the industrial reality. For that reason, it is proposed the use of metaheuristics as an alternative approach in this problem with the aim to determine, with a low computational effort, the best assignation of the analysis in order to minimize the makespan and weighted total tardiness simultaneously. These optimization objectives will allow this labora-tory to improve their productivity and the customer service, respectively. A Ant Colony Optimization algorithm (ACO) is proposed. Computational experiments are carried out comparing the proposed approach versus exact methods. Results show the efficiency of our ACO algorithm

On green routing and scheduling problem

The vehicle routing and scheduling problem has been studied with much interest within the last four decades. In this paper, some of the existing literature dealing with routing and scheduling problems with environmental issues is reviewed, and a description is provided of the problems that have been investigated and how they are treated using combinatorial optimization tools

Multi-Objective and Multi-Attribute Optimisation for Sustainable Development Decision Aiding

Optimization is considered as a decision-making process for getting the most out of available resources for the best attainable results. Many real-world problems are multi-objective or multi-attribute problems that naturally involve several competing objectives that need to be optimized simultaneously, while respecting some constraints or involving selection among feasible discrete alternatives. In this Reprint of the Special Issue, 19 research papers co-authored by 88 researchers from 14 different countries explore aspects of multi-objective or multi-attribute modeling and optimization in crisp or uncertain environments by suggesting multiple-attribute decision-making (MADM) and multi-objective decision-making (MODM) approaches. The papers elaborate upon the approaches of state-of-the-art case studies in selected areas of applications related to sustainable development decision aiding in engineering and management, including construction, transportation, infrastructure development, production, and organization management

2015 GREAT Day Program

SUNY Geneseo’s Ninth Annual GREAT Day.https://knightscholar.geneseo.edu/program-2007/1009/thumbnail.jp

Intelligent simulation of coastal ecosystems

Tese de doutoramento. Engenharia Informática. Faculdade de Engenharia. Universidade do Porto, Faculdade de Ciência e Tecnologia. Universidade Fernando Pessoa. 201