Roberto Fernandes Tavares Neto

JOINT OPTIMIZATION OF PRODUCTION PLANNING AND VEHICLE ROUTING PROBLEMS: A REVIEW OF EXISTING STRATEGIES

Keen competition and increasingly demanding customers have forced companies to use their resources more efficiently and to integrate production and transportation planning. In the last few years more and more researchers have also focused on this challenging problem by trying to determine the complexity of the individual problems and then developing fast and robust algorithms to solve them. This paper reviews existing literature on integrated production and distribution decisions at the tactical and operational level, where the distribution part is modelled as some variation of the well-known Vehicle Routing Problem (VRP). The focus is thereby on problems that explicitly consider deliveries to multiple clients in a less-than-truckload fashion. In terms of the production decisions we distinguish in our review between tactical and operational production problems by considering lot-sizing/capacity allocation and scheduling models, respectively.

A software model to prototype ant colony optimization algorithms

The study of multi-agent systems usually begins by implementing a base-algorithm, which is changed as required by the aim of the research. In this context, carrying out different algorithms, which have already been established, is not a trivial task as it requires implementing these algorithms. This paper presents a software model that allows one to prototype variations of the Ant Colony Optimization metaheuristic. This model can be used to avoid implementations in duplicity, allowing, with less effort, the generation of different algorithms to be used on the same problem. Results shown that, specially for more elaborated algorithms, the adoption of the proposed software model reduce significantly the coding effort required.

Otimização por colônia de formigas para o problema de sequenciamento de tarefas em uma única máquina com terceirização permitida

This paper considers the problem of scheduling a set of tasks on a single machine environment with outsource allowed. This multicriteria problem, defined as 1 / Budget / (1 - δ) Σ Cj + δ. OC, aims to minimize the weighted sum of total outsourcing costs and the sum of individual completion times. To solve this problem, a two-stage method is proposed: the first stage orders the tasks using the SPT (Shortest Processing Time) rule. The second stage uses an ACO (Ant Colony Optimization) algorithm to decide whether the job will be outsourced by using four problem-specific variations: i) a graph-representation of scheduling problems for scheduling problems with outsourcing allowed; ii) a pre-selection rule that guarantees the viability of the solution; iii) a new problem-specific visibility rule; and iv) a local search strategy. The implementation of this method produces better results than those obtained by Lee and Sung (2008a), the only paper found in the literature that deals with this problem. Moreover, the local search procedure was able to improve the results for medium and large problem sets.

Proposta de um framework para prototipagem de sistemas heurísticos multiagentes baseados em algorítmos de colônia de formigas

The study of multi-agent systems usually begins by implementing a base-algorithm, which is changed as required by the aim of the research. In this context, carrying out different algorithms, which have already been established, is not a trivial task as it requires implementing these algorithms.This article proposes a computer framework that enables one to prototype a large set of heuristics based on the Ant Colony System metaheuristic. As an example of the proposed framework, four important AS algorithms were implemented. The results show a significant reduction in the implementation time by using the proposed framework.