The goal of our research is to develop a collection of software tools to be integrated into the existing industrial software environment to support terminal operators in making strategic decisions about resource allocation and terminal organization. We believe that the first important step in this process is to define a simulation tool to plan and optimize the placement of containers in the terminal. The decision about where a container is to be placed in the terminal yard depends on many parameters: the present occupancy level of the container area (or cluster), the final destination of the containers, the best position to dock the ship, the container's size, the container's content and so on. The problem is difficult because of the competing nature of these parameters and because the containers arrive some weeks before the ship's actual arrival date. In this paper, we describe the use of genetic algorithms (GAs) to perform two tasks: planning (or scheduling) the cluster creation and optimally locating the clusters in the yard. We discuss each GA in detail and present preliminary results.

This paper proposes an advanced decision system, called Virtual Dynamic Store (VDS), for supporting retail store management. The VDS architecture supports the decision processes within retail stores by providing users with three main functionalities: store layout analysis, item and shelf management, and store monitoring and control by real-time simulation (or remote control by on-line simulation). As additional functionality, not related to the decision process within a retail store, the VDS architecture could also be used as a virtual web shop for e-commerce. To provide evidence on the relevance of the VDS, the architecture is tested within a real store by proposing four different application examples that show the potential of the VDS as an advanced decision support system.

This paper focuses on the development of a new generation of interoperable simulators of micro activities in a logistics node; the proposed example focuses on a real-time full-scope virtual simulator of port activities able to simulate the activities of the whole port by having ships, cranes, trucks and containers interoperating in a federation. The technologies adopted in terms of architecture and installation were very effective in creating a mobile laboratory open to further extension by online interoperation with other simulators and with biomedical devices for assessing human capabilities within this framework. This approach allows us to face the existing challenges in extending the capabilities of a logistics node over their current capabilities limited by technological and human factors

The freight logistics includes all the processes needed to supply industry, retailers and wholesalers and final customers with goods. Such processes generate a flow of goods that, in the global supply chain, mainly relies on the activities carried out within worldwide container terminals. In this paper, the authors present a simulation model of a real container terminal. After some preliminary analyses, the simulation model is first used with Design of Experiments and Analysis of Variance to investigate the effects of different resources allocations (i.e., number of forklifts and tractors) and some parameters (i.e., inter-arrival times, container unloading time) on the container terminal performances in terms of total number of handled containers per day. Then, based on the results achieved through the Design of Experiments and Analysis of Variance, the simulation model is used with genetic algorithms to carry out a range allocation optimization on berth assignment to incoming ships and number of tractors serving each quay crane. The aim of the optimization is the minimization of the average time spent by each ship in the port area (decreasing, as consequence, costs and increasing service level provided to final customers).

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