a b s t r a c tElectric vehicle-sharing systems have been introduced to a number of cities as a means of increasing mobility, reducing congestion, and pollution. Electric vehicle-sharing systems can offer one or two-way services. One-way systems provide more flexibility to users since they can be dropped-off at any station. However, their modeling involves a number of complexities arising from the need to relocate vehicles accumulated at certain stations. The planning of one-way electric vehicle-sharing systems involves a host of strongly interacting decisions regarding the number, size and location of stations, as well as the fleet size.In this paper we develop and solve a multi-objective MILP model for planning one-way vehicle-sharing systems taking into account vehicle relocation and electric vehicle charging requirements. For real world problems the size of the problem becomes intractable due to the extremely large number of relocation variables. In order to cope with this problem we introduce an aggregate model using the concept of the virtual hub. This transformation allows the solution of the problem with a branch-and-bound approach.The proposed approach generates the efficient frontier and allows decision makers to examine the trade-off between operator's and users' benefits. The capabilities of the proposed approach are demonstrated on a large scale real world problem with available data from Nice, France. Extensive sensitivity analysis was performed by varying demand, station accessibility distance and subsidy levels. The results provide useful insights regarding the efficient planning of one-way electric vehicle-sharing systems and allow decision makers to quantify the trade-off between operator's and users' benefits.

If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this paper is threefold: first, review the literature on the topic of behavioural antecedents of collaboration and their impact on supply chain integration and performance; second, lay the theoretical foundations and develop a conceptual model linking behavioural antecedents of collaboration, information integration, coordination of operational decisions and supply chain performance; and third, set out operationalisation considerations. Design/methodology/approach -A conceptual model with theoretical basis on Relational Exchange Theory (RET) and extant supply chain theory is developed as a causal model that can be operationalised using structural equations modelling (partial least squares) and a "single key informant" approach. Findings -Positive relationships between behavioural antecedents of collaboration (trust, commitment, mutuality/reciprocity), information integration, coordination of operational decisions and supply chain performance (efficiency, effectiveness) are hypothesised. RET provides adequate theoretical background that leads to the theoretical establishment of hypotheses between behavioural antecedents, supply chain integration and performance, which are worth testing empirically.Research limitations/implications -The ideas presented in this paper enrich the study of behavioural factors in supply chain management and their impact on supply chain performance, and may benefit researchers in the field. The paper also sets the scene (experimental design, measurement items) for the upcoming field research. The empirical part of the work will provide the necessary evidence for the validation of the established hypotheses. Practical implications -The proposed linkages may stimulate the interest of supply chain strategists towards more collaborative relationship management and affect their decisions on the behavioural antecedents of relationship formation and management. Moreover, the proposed model may help clarify how the integration of critical operational contingencies -information, operational decisions -can help achieve superior supply chain performance. justification on the development of knowledge that will assist decision making in SCM/...

a b s t r a c tOne-way electric vehicle carsharing systems are receiving increasing attention due to their mobility, environmental, and societal benefits. One of the major issues faced by the operators of these systems is the optimization of the relocation operations of personnel and vehicles. These relocation operations are essential in order to ensure that vehicles are available for use at the right place at the right time. Vehicle availability is a key indicator expressing the level of service offered to customers. However, the relocation operations, that ensure this availability, constitute a major cost component for the provision of these services. Therefore, clearly there is a trade-off between the cost of vehicle and personnel relocation and the level of service offered. In this paper we are developing, solving, and applying, in a real world context, an integrated multi-objective mixed integer linear programming (MMILP) optimization and discrete event simulation framework to optimize operational decisions for vehicle and personnel relocation in a carsharing system with reservations. We are using a clustering procedure to cope with the dimensionality of the operational problem without compromising on the quality of the obtained results. The optimization framework involves three mathematical models: (i) station clustering, (ii) operations optimization and (iii) personnel flow. The output of the optimization is used by the simulation in order to test the feasibility of the optimization outcome in terms of vehicle recharging requirements. The optimization model is solved iteratively considering the new constraints restricting the vehicles that require further charging to stay in the station until the results of the simulation are feasible in terms of electric vehicles' battery charging levels. The application of the proposed framework using data from a real world system operating in Nice, France sheds light to trade-offs existing between the level of service offered, resource utilization, and certainty of fulfilling a trip reservation.

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We survey research on hazardous materials transportation in the areas of risk analysis, routing/scheduling and facility location. Our focus is primarily on work done since 1980, and on research which is methodological rather than empirical. We also limit our focus to transport by land-based vehicles (truck and rail), excluding pipeline, air and maritime movements. The review traces the evolution of models from single-criterion optimizations to multiobjective analyses, and highlights the emerging direction of dealing explicitly with distributions of outcomes, rather than simply optimizing expected values. We also indicate examples of work which integrate risk analysis with routing, and routing with facility location. We conclude with a discussion of several aspects of hazardous materials transportation which offer important challenges for further research.