"Incentivized Sustainable Mobility" is a conceptual business model which involves four stakeholders: citizens, municipalities, commerce and mobility services. A platform named "ISUMO" (Incentivized Sustainable Mobility) provides technological support to this business model, integrating a set of metaservices that unifies the existing ICTs of transportation plus a unique patented QR-based (Quick Response) low-cost charging device for electric vehicles. Essentially, the system tracks and registers citizens' transportation activities (anonymously and voluntarily) and evaluates each through a scoring system while their ecological footprint is calculated. Afterwards, citizens are able to exchange their accumulated points for discount QR coupons, to be redeemed in the associated commerce in order to purchase their products or services. The breakthrough of this business model is that it enhances awareness of sustainable mobility practices, increasing their attractiveness as perceived by the stakeholders with diverse benefits; citizens (and indirectly, the municipalities) initiate a new consumption pattern of "coupons culture" linked to sustainable mobility, the urban economy is stimulated, and the use of mobility services grows, providing a new business opportunity regarding electric vehicles. It is expected that continuous exploration of the model and implementation will contribute to sustainable social and economic development aiming at CO2 emissions reduction, headline targets of the Europe 2020 strategy. OPEN ACCESSSustainability 2015, 7 6120

This paper examines a scheduling problem from a fine chemicals company that synthesizes active pharmaceutical ingredients. The main goal is to select from the set of available equipment units, those units that are better-suited for the production of the ingredient being considered. A minimum number of them maximizes plant flexibility by leaving some free capacity to respond faster to other product orders, but also increases the makespan, because significant changeover times are mandatory. A tradeoff is thus involved that is quantified by an objective function that minimizes a weighted sum of the total equipment allocation cost plus the makespan, which is penalized with a cost factor. Because several product batches are needed, a stable mode of operation is assumed, with most of the schedule being derived by repetition of an optimal production pattern. This is obtained through the use of a resource-task network discrete-time periodic scheduling formulation that generates a mixed-integer linear program (MILP). For this particular case study, it is shown that the periodic schedule contains all the necessary information for easily deriving the startup and shutdown phases of production. The results have shown that the industrial problem is tractable and that a few minutes of computational time are sufficient to determine the optimal cycle time and corresponding schedule. To allow for more-complex problems to be tackled, a new decomposition strategy is proposed that reduces the computational effort by one order of magnitude without severely compromising optimality.

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This paper deals with the design and implementation of a data model and operations for dealing with continuously changing spatial data in Oracle 11g object-relational DBMS. The data model relies on abstract data types but we introduce modifications to the internal structure of the spatiotemporal data representations proposed in the literature, to reduce storage requirements and to enable the reuse of data during the execution of queries. We show how to implement spatiotemporal operations relying on the spatial functions released by the underlying DBMS and how to use the alternative data representations to reduce the volume of temporary data created in the evaluation of spatiotemporal operations. We also demonstrate how to use the proposed data types and operations for storage and manipulation of moving objects data using SQL. Finally, we discuss on the advantages and disadvantages of the proposed solutions.