One-way Vehicle Sharing Systems (VSS), such as Vélib’ Paris, have a poor performance without regulation. We want to improve the efficiency of VSS using design strategies or pricing as incentive. Stochastic models are intractable for the size of systems we want to tackle. We therefore discuss a scenario-based approach, i.e. off-line deterministic optimization problems on a given stochastic reali...

Software components can be connected by XML processing pipelines, which may perform adaptations. In our model, individual pipeline stages serialize source data structures to XML, perform one or multiple XSL transformations, transport the message to its destination and finally deserialize it to target data structures. Implementation of this model is open to optimizations. The present paper discu...

This paper considers a scheduling problem with uncertain processing times and machine breakdowns in industriall/office workplaces and solves it via a novel robust optimization method. In the traditional robust optimization, the solution robustness is maintained only for a specific set of scenarios, which may worsen the situation  for new scenarios. Thus, a two-stage predictive algorithm is prop...

We consider the Courier Delivery Problem, a variant of the Vehicle Routing Problem with time windows in which customers appear probabilistically and their service times are uncertain. We use scenario-based stochastic programming with recourse to model the uncertainty in customers and robust optimization for the uncertainty in service times. Our proposed model generates a master plan and daily s...

this paper discusses the portfolio selection based on robust optimization. since the parameters values of the portfolio optimization problem such as price of the stock, dividends, returns, etc. of per share are unknown, variable and their distributions are uncertain because of the market and price volatility, therefore, there is a need for the development and application of methodologies for de...

in this paper, a robust model presented is developed for hub covering flow problem in which hubs have capacity. this problem has two objective functions converting to a single-objective problem by using weighting method. firstly, the problem will be formulated in a certain case. then, by considering the demand as a non-random variable, it will be modeled by robust optimization. finally, by usin...

The critical node selection problem (CNP) has important applications in telecommunication, supply chain design, and disease propagation prevention. In practice, the weights on the connections are either uncertain or hard to estimate so recently robust optimization approaches have been considered for CNP. In this article, we address very general uncertainty sets, only requiring a linear optimiza...

Demand for supplies, such as ammunition, during a military operation is a scenario-dependent random variable that may be subject to high variance. The challenge is to design an efficient military logistics supply chain that satisfies uncertain, nonstationary demands, while taking into account the volatility and singularity of military operations. This research focuses on the development of a mo...

We develop a scenario optimization model for asset and liability management of individual investors. The individual has a given level of initial wealth and a target goal to be reached within some time University of Palermo,IT. [email protected] Prometeia, Bologna, IT. [email protected] University of Cyprus, Nicosia, CY, and The Financial Institutions Center, The Wharton School, Philadelphia...

The present article formulates the scenarios that the organization will be probably facing with, using the uncertain factors in business environment, and it also selects the most robust strategies of organization for dealing with the formulated scenarios using the fuzzy information expressed by the experts in fuzzy inference system. The present article aims to provide a method enabling the scen...