We improve the mixed-integer programming formulation of the multicommodity capacitated fixed-charge network design problem by incorporating valid inequalities into a cutting-plane algorithm. We use five classes of known valid inequalities: the strong, cover, minimum cardinality, flow cover, and flow pack inequalities. The first class is particularly useful when a disaggregated representation of the commodities is chosen, and the last four are expressed in terms of network cut sets. We develop efficient separation and lifting procedures for these classes of inequalities. We present computational results on a large set of instances of various characteristics, allowing us to measure the impact of the different classes of valid inequalities on the quality of the lower bounds, in particular with respect to the representation of the commodities.
This article describes the STAN (Strategic Transportation ANalysis) program, which analyses the factors affecting freight carriers, and helps to make their operations more efficient and economical. STAN was developed at the University of Montreal, and has been used successfully in several developed and developing countries. It is a decision support system, which provides uniform and efficient data handling procedures, including complete validation of data consistency during data entry. Its database principally contains networks, matrices and functions, and is structured to allow the simultaneous analysis of several planning alternatives. STAN can digitise networks directly from maps, and allows all aspects of the database to be listed and visualised graphically. Its multimodal network permits parallel links between adjacent nodes, with one model per link. It can use intermodal transfers to build multi-modal paths from origins to destinations. Its simulation of flows is performed by multi-mode multi-product assignment procedures with nonlinear cost functions. Its wide variety of results includes: (1) the interactive comparison of scenarios using graphical displays; (2) economic evaluation; and (3) interactive shortest path calculations. For the covering abstract see IRRD 871197.
Stochastics affects the optimal design of a network. This paper examines the single-source single-commodity stochastic network design problem. We characterize the optimal designs under demand uncertainty and compare with the deterministic counterparts to outline the basic structural differences. We do this partly as a basis for developing better algorithms than are available today, partly to simply understand what constitutes robust network designs.
The authors present in this paper a normative model for simulating freight flows of multiple products on a multimodal network. The multimodal aspects of the transportation system considered are accounted for in the network representation chosen. The multiproduct aspects of the model are exploited in the solution procedure, which is a Gauss-Seidel-Linear Approximation Algorithm. An important component of the solution algorithm is the computation of shortest paths with intermodal transfer costs. Computational results obtained with this algorithm on a network that corresponds to the Brazil transportation network are presented. (A)
We present a three-layer taxonomy of City Logistics projects that provides the means to explore the similarities and differences in the elements characterizing the various City Logistics initiatives as a step towards better understanding and predicting their performance. To illustrate its interest, the taxonomy is used to describe well-known systems and identify a number of trends in the evolution of City Logistics.
