A Supporting Decisions Platform for the Design and Optimization of a Storage Industrial System

Warehouses are one of the most critical resources in production systems, whose performance significantly depend on the availability of materials in the right location, in the right quantity and at the right time. Literature presents many contributions for the design and control of a storage system, but a few of them discuss on the importance of an integrated approach based on the adoption of different supporting decisions models and tools, from mixed integer linear programming (MILP) to visual interactive simulation (VIS), passing through heuristic procedures and cluster analysis (CA). This chapter presents a conceptual and integrated framework for the design, management, control and optimization of both manual, i.e. man-on-board, picker to part and automated, i.e. part to picker, storage systems, both unit-load and less than unit-load order picking systems (OPS), by the development and application of different models and tools. The proposed framework integrates the management decisions in order to find not a system configuration as a result of local optima, but the minimal cost warehousing system as a result of the following integrated decisions: the space allocation to the forward area and the bulk area in a OPS, the system layout, the storage allocation within each area, i.e. the determination of the storage level devoted to a stock keeping unit (sku) both in fast pick area and in reserve area, the storage locations assignment, i.e. the determination of the warehousing system location to be assigned to a sku, the routing policies, the operating procedures, etc. A discussion on supporting decisions models and tools useful for practitioners of industry to face these critical problems is presented and finally a case study illustrated

Pricing visitor preferences for temporary art exhibitions

This paper focuses on the initiatives that museum managers may implement to maximize the profits of museums located in tourist destinations and that host temporary art exhibitions. These initiatives have direct effects on visitor demand and indirect effects on the tourist destination. Classifying visitors into residents, excursionists and tourists, the authors evaluate their preferences and willingness to pay for managerial initiatives. They focus specifically on for-profit museums that host temporary exhibitions in medium and small tourist destinations. Visitor preferences are priced through discrete choice experiments submitted to a sample of (actual and potential) visitors to Castel Sismondo Museum in Rimini, Italy