A well-known traffic simulation model bases on the idea to represent street sections by so-called cells where vehicles are streaming from one cell to another in order to give a realistic image of traffic flows. Its basic ideas were picked up recently to formulate an optimization model for evacuationplanning purposes. We will address three major weaknesses of the recent model, namely the usage of afixed single cell size, missing consideration of lanes as well as missing limitations for traffic flows andshow how to overcome them. Stimulated by this, we formulate the extended Cell-Transmission-Based Evacuation Planning Model and a new optimization model to facilitate this model in terms of choosing the optimum cell size. Additionally, we will present an iterative simulation-based optimization approach in order to evaluate and to enhance results in a more realistic environment. This approach takes advantage of a standalone vehicle reallocation optimization model, additional traffic flow limitations as well as a state-of-the-art microscopic traffic simulation. We will demonstrate the effectiveness of this approach in a real-world example.

A huge number of publications deal with project scheduling and very often the objective is to minimize the makespan. We claim that in the real world money counts. Therefore, we review how project payments can be defined in practice. The issues of contracting and bidding are discussed to demonstrate that a whole universe of specific model formulations would be needed to cover real situations.

O presente artigo apresenta, modela matematicamente e soluciona um problema multi-nível integrado de dimensionamento de lotes e programação da produção em um ambiente industrial com máquinas paralelas que apresentam restrições de capacidade, custos e tempos de preparo dependentes da seqüência. O problema é motivado pela realidade encontrada em alguns setores industriais, em particular o de fabricação e engarrafamento de bebidas. Nesse tipo de indústria a produção envolve dois níveis interdependentes com decisões relativas à armazenagem das matérias-primas e ao engarrafamento das bebidas. As diversas matérias-primas são armazenadas em tanques de onde escoam para as linhas de engarrafamento. O desafio é determinar simultaneamente o dimensionamento e a programação de custo mínimo das matérias-primas nos tanques e o envasamento de bebidas nas linhas, onde tempos e custos de trocas dependem do tipo de item previamente armazenado e envasado. É proposto um modelo matemático inteiro-misto que introduz diversas restrições combinadas que até então costumavam ser tratadas separadamente na literatura. A não existência de testes com modelos similares nos obrigou a criar um conjunto de instâncias para avaliar o modelo e as técnicas de solução propostas. As instâncias foram solucionadas otimamente por meio do pacote computacional GAMS/Cplex. A solução exata se mostrou viável apenas em instâncias de pequena dimensão devido à complexidade do problema em estudo. Os resultados computacionais obtidos pelo GAMS/Cplex são apresentados e analisados.

The present paper establishes, describes mathematically and solves a multi-level lot sizing and scheduling problem in an industrial set with parallel machines and sequence-dependent setup cost and time. The problem is motivated by real situations found in some industrial settings mainly the soft drink industry. In this kind of industry, the production involves two interdependent levels with decisions about raw material storage and soft drink bottling. The several raw materials are stored in tanks from which they flow to the bottling lines. The challenge is to determine simultaneously the minimum cost lot sizing and scheduling of raw material in tanks and also in the bottling lines, where setup costs and time depend on the previous items stored and bottled. A mixed-integer mathematical model with several combined constrains that use to be handled apart in the literature is proposed. The lack of similar models led us to create a set of instances to evaluate the model and the solution techniques developed. The instances were optimally solved by the GAMS/Cplex software. Due to the problem complexity, it is demonstrated that the use of this optimization package is only viable for small-sized instances. The computational results are showed and analyzed.