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Freire, A. S., Moreno, E., & Vielma, J. P. (2012). An integer linear programming approach for bilinear integer programming. Oper. Res. Lett., 40(2), 74–77.
Abstract: We introduce a new Integer Linear Programming (ILP) approach for solving Integer Programming (IP) problems with bilinear objectives and linear constraints. The approach relies on a series of ILP approximations of the bilinear P. We compare this approach with standard linearization techniques on random instances and a set of real-world product bundling problems. (C) 2011 Elsevier B.V. All rights reserved.
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Moreno, E., Beghelli, A., & Cugini, F. (2017). Traffic engineering in segment routing networks. Comput. Netw., 114, 23–31.
Abstract: Segment routing (SR) has been recently proposed as an alternative traffic engineering (TE) technology enabling relevant simplifications in control plane operations. In the literature, preliminary investigations on SR have focused on label encoding algorithms and experimental assessments, without carefully addressing some key aspects of SR in terms of the overall network TE performance. In this study, ILP models and heuristics are proposed and successfully utilized to assess the TE performance of SR-based packet networks. Results show that the default SR behavior of exploiting equal cost multiple paths (ECMP) may lead to several drawbacks, including higher network resource utilization with respect to cases where ECMP is avoided. Moreover, results show that, by properly performing segment list computations, it is possible to achieve very effective TE solutions by just using a very limited number of stacked labels, thus successfully exploiting the benefits of the SR technology. (C) 2017 Elsevier B.V. All rights reserved.
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Pereira, J., & Vila, M. (2016). A new model for supply chain network design with integrated assembly line balancing decisions. Int. J. Prod. Res., 54(9), 2653–2669.
Abstract: Supply chain network design aims at the integration of the different actors of a supply chain within a single framework in order to optimise the total profit of the system. In this paper, we consider the integration of line balancing issues within the tactical decisions of the supply chain, and we offer a novel model and a solution approach for the problem. The new approach decomposes the problem into multiple line balancing problems and a mixed integer linear model, which is easier to solve than the previously available non-linear mixed integer formulation. The results show that the new method is able to solve previously studied models within a fraction of the reported running times, and also allows us to solve larger instances than those reported in earlier works. Finally, we also provide some analysis on the influence of the cost structure, the demand and the structure of the assembly process on the final configuration of the assemblies and the distribution network.
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Tarifeno-Gajardo, M., Beghelli, A., & Moreno, E. (2016). Availability-Driven Optimal Design of Shared Path Protection in WDM Networks. Networks, 68(3), 224–237.
Abstract: Availability, defined as the fraction of time a network service is operative, is a key network service parameter. Dedicated protection increases availability but also the cost. Shared protection instead decreases the cost, but also the availability. In this article, we formulate and solve an integer linear programming (ILP) model for the problem of minimizing the backup resources required by a shared-protected static optical network whilst guaranteeing an availability target per connection. The main research challenge is dealing with the nonlinear expression for the availability constraint. Taking the working/backup routes and the availability requirements as input data, the ILP model identifies the set of connections sharing backup resources in any given network link. We also propose a greedy heuristic to solve large instances in much shorter time than the ILP model with low levels of relative error (2.49% average error in the instances studied) and modify the ILP model to evaluate the impact of wavelength conversion. Results show that considering availability requirements can lead up to 56.4% higher backup resource requirements than not considering them at all, highlighting the importance of availability requirements in budget estimation. (C) 2016 Wiley Periodicals, Inc.
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