A Topological Method to Choose Optimal Solutions after Solving the Multi-criteria Urban Road Network Design Problem

The paper proposes and applies a method for systematically sorting and reducing the number of different possible solutions to a network design problem (NDP). This is achieved first by defining a topological similarity measurement and then by applying cluster analysis. The NDP can be derived from the scientific literature. In general, the method consists of some models and subsequent algorithms that generate different solutions (enumerative, branch and bound, genetic, expert panel, ...) and evaluate for each solution an objective function (with deterministic or stochastic network assignment and with elastic or inelastic demand). The NDP, mainly in urban areas, needs multi-criteria evaluation and in each case a large set of non-dominated solutions is generated. In this paper, in order to select solutions and identify latent optimal network layouts, cluster analysis is carried out. The methodology utilises a “cluster” formation in relation to the solution topology and a “best” (representative) solutions extraction in relation to the criteria values. It can be utilised after solving the existing multi-criteria NDP and in other network problems, where the best solutions (for global or local network layouts) are extracted (with respect to the network topology) from a large set. The method is applied in a test system and on different real networks in two Italian towns, in order to analyse the goodness of the solution algorithm and assess its possible application to different networks.     

A model system for the ex-ante assessment of city logistics measures

This paper proposes a model system developed in order to support ex-ante assessment of city logistics measures. The model system allows us to simulate the choices of each decision-maker involved in the urban freight transport and logistics and to investigate how the policies and the following measures can influence her/his choices.The model system is an open architecture and consists of two levels: commodity and vehicle. The commodity level allows us to analyse the attraction and acquisition movements taking into account the effects due to city logistics policy implementation affecting the end-consumer and retailer/wholesaler/producer (restocker) choices. The freight sold in each urban shop (or in general urban business) is estimated starting from consumption demand and, then, the restocker’s choices for restocking are analysed in depth. The vehicle level focuses on the restocking process and the links between retailer and wholesaler/producer operating in the study area. This level allows us to investigate the impacts of implementing city logistics measures on journey time, timing and path used for restocking the urban retail businesses.     

Optimal management of human resources in transhipment container ports

Human resources allocation plays a key role in transhipment maritime container terminals to achieve high levels of productivity and provide high quality services to shipping companies. The deep interest of container terminals in this issue can be supported by optimization methods. In this work, an optimization model is proposed to determine the optimal daily allocation of crane operators and trailer drivers. Different requirements are taken into account for permanent staff, external workers and personnel shortfall. Since workforce undermanning is a crucial factor for both shipping companies and container terminals, we aim to show that personnel shortfalls and operation delays can be significantly reduced if the model encompasses a longer-than-1-day planning horizon in a rolling horizon fashion.