Samuel Vieira Conceição

The vehicle routing problem with hard time windows and stochastic travel and service time

Statistic model to sum a truncated non-normal with a normal distribution.Detailed application of the statistic model to solve the stochastic VRP.Computational experiments with comprehensible analysis of the results. In real-world environments, the variability is always present and influences the level and cost service offered to customers. In this scenario, the present work develops a strategy to solve the Vehicle Routing Problem with Time Windows (VRPTW) in which the travel time among the customers is known only probabilistically and the vehicles are not allowed to start the service before the earliest time windows. The fact there is waiting time brings a challenge to the model because the arrival time distribution at a customer can be truncated, affecting the arrival time in the following customers. A new method is developed to estimate the vehicle arrival time at each customer and to estimate the vehicles probability to respect the customers time window. The metaheuristic based on Iterated Local Search finds the best route with minimal expected cost, and it guarantees that certain levels of service are met. A benchmark is used to evidence the superior performance and accuracy of the proposed method.

Avaliação do desenpenho logístico da cadeia brasileira de suprimentos de refrigerantes

Esse artigo tem como objetivo avaliar o desempenho logistico de quatro elos da cadeia brasileira de suprimentos de refrigerantes (fornecedores de embalagem para refrigerantes, industria de refrigerantes, atacado e supermercado), adotando como metodologia o survey eletronico. As repostas foram analisadas utilizando-se os testes estatisticos Mann-Whitney e Kruskal-Wallis, alem de uma analise descritiva dos dados e da realizacao dos testes de hipotese. As empresas avaliaram o desempenho logistico da cadeia, por meio de indicadores da logistica interna e externa, e identificaram a percentagem de uso desses indicadores. A taxa media de respostas foi de 40%. A pesquisa mostrou que os elos da cadeia de refrigerantes utilizam mais os indicadores de desempenho, que avaliam a logistica interna, do que os que avaliam a logistica externa.

A mixed load capacitated rural school bus routing problem with heterogeneous fleet

Brazil is improving its service level for its rural school transportation system.Five algorithms based on meta-heuristics are devised to address the problem.Two different transportation approaches are analyzed: single and mixed load plans.The mixed load plan has lower costs, number of buses and student riding distances.The mixed load approach shows to be more suitable for the Brazilian context. A capacitated rural school bus routing problem featuring mixed loads, a heterogeneous fleet, and the same school starting time is here addressed. This is an important problem of the routing literature which has been attracting the attention of many researchers recently. The mixed load feature allows students from different schools to ride the same bus at the same time. Five meta-heuristic based algorithms were devised to solve the problem, and evaluated on solving four different datasets, one of them being based on a real case from Brazil. Four traditional local search neighborhood structures for vehicle routing problems were adapted and specialized to handle mixed loads and a heterogeneous fleet simultaneously. To the best of the authors knowledge, it is the first time that both features are treated jointly within an algorithm, and not as a post processing optimization step. The attained cost savings and reduction of fleet sizes suggest the suitability of a mixed load, heterogeneous fleet approach for sparsely populated rural areas. Moreover the devised framework has been embedded into a decision support system which is assisting several municipalities of the state of Minas Gerais, Brazil, to better plan their routes and reduce transportation costs.

Hub location under hub congestion and demand uncertainty: the Brazilian case study

In this work, a mixed integer nonlinear programming model combining direct service links, demand uncertainty and congestion effects is proposed. This model is efficiently solved by Generalized Benders Decomposition, for instances of moderate sizes and reasonable number of scenarios. The deployed algorithms are further used for re-designing the Brazilian air transportation network, enabling the analysis of future demand scenarios and providing decision support about the optimal investment policy for Brazil.

The facility location problem in the steel industry: a case study in Latin America

In this article, we present a case study in a complex and diversified multinational steel company using a deterministic formulation for a capacitated location problem based on a model discussed in the literature. The objective is to determine the quantity and location of distribution centres needed to serve a customer base within specified service levels. A large amount of data about the existing distribution network is gathered and modelled. A decision support system based on mixed-integer programming was used to solve the problem. One of the main contributions of this article concerns the manipulation of a large real database to extract enough information to obtain an acceptable model to solve a complex problem of a steel industry based on adaptations and improvements of a model offered in the literature.

A multi-objective capacitated rural school bus routing problem with heterogeneous fleet and mixed loads

Four multi-objective meta-heuristic algorithms are presented to solve a multi-objective capacitated rural school bus routing problem with a heterogeneous fleet and mixed loads. Three objectives are considered: the total weighted traveling time of the students, the balance of routes among drivers, and the routing costs. The proposed methods were compared with one from the literature, and their performance assessed observing three multi-objective metrics: cardinality, coverage, and hyper-volume. All four devised methods outperformed the one from the literature. The algorithm with a path relinking procedure embedded during the crowding distance selection scheme had the best overall performance.

A demand classification scheme for spare part inventory model subject to stochastic demand and lead time

In this study, we aim to develop a demand classification methodology for classifying and controlling inventory spare parts subject to stochastic demand and lead time. Using real data, the developed models were tested and their performances were evaluated and compared. The results show that the Laplace model provided superior performance in terms of service level, fill rate (FR) and inventory cost. Compared with the current system based on normal distribution, the proposed Laplace model yielded significant savings and good results in terms of the service level and the FR. The Laplace and Gamma optimisation models resulted in savings of 82 and 81%, respectively.

Otimização do fluxo de materiais através da manufatura celular

Machine layout in a job shop production system is basically a process where machines performing similar processes are grouped together. By physically grouping identical machines together, this production systems offers a high degree of flexibility. However, this flexibility entails many problems, such as high setup costs, inefficient material flow, high inventory cost and low productivity. To circumvent the above mentioned problems, this paper presents a methodology based on production flow analysis. The experimental study took place in a corporation of the furniture industry. The results on cellular manufacturing and production flow analysis show that this methodology was able to reduce material handling time, setup time and throughput time. In addition, a new cellular layout was achieved.

Flexibility evaluation of multiechelon supply chains

Multiechelon supply chains are complex logistics systems that require flexibility and coordination at a tactical level to cope with environmental uncertainties in an efficient and effective manner. To cope with these challenges, mathematical programming models are developed to evaluate supply chain flexibility. However, under uncertainty, supply chain models become complex and the scope of flexibility analysis is generally reduced. This paper presents a unified approach that can evaluate the flexibility of a four-echelon supply chain via a robust stochastic programming model. The model simultaneously considers the plans of multiple business divisions such as marketing, logistics, manufacturing, and procurement, whose goals are often conflicting. A numerical example with deterministic parameters is presented to introduce the analysis, and then, the model stochastic parameters are considered to evaluate flexibility. The results of the analysis on supply, manufacturing, and distribution flexibility are presented. Tradeoff analysis of demand variability and service levels is also carried out. The proposed approach facilitates the adoption of different management styles, thus improving supply chain resilience. The model can be extended to contexts pertaining to supply chain disruptions; for example, the model can be used to explore operation strategies when subtle events disrupt supply, manufacturing, or distribution.

Reconfiguração dinâmica de linhas de montagem

In this paper we present a new problem involving assembly lines. It arises when successive variations in the cycle time force line re-configuration. We propose four mixed integer programming formulations for the problem, three of them using a time horizon divided in periods. Such assumption gives the problem a dynamic character. The models try to smooth the workload among the stations by forcing it to fall between minimum and maximum values predefined by the user. They were implemented in a commercial package for mathematical programming and some results are reported. Comparisons were made against the repetitive use of classical models (SALBP like) to demonstrate the superiority of this new approach.