Journal: European Journal of Operational Research

Abbreviation

Eur. J. oper. res.

Publisher

Elsevier

Journal Volumes

ISSN

0377-2217
1872-6860

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Publications 1 - 10 of 51
  • Solving the fixed rank convex quadratic maximization in binary variables by a parallel zonotope construction algorithm
    Item type: Conference Paper
    Ferrez, J.A.; Fukuda, K.; Liebling, T.M. (2005)
    European Journal of Operational Research
  • Market-based coordination of integrated electricity and natural gas systems under uncertain supply
    Item type: Journal Article
    Ordoudis, Christos; Delikaraoglou, Stefanos; Kazempour, Jalal; et al. (2020)
    European Journal of Operational Research
    © 2020 Elsevier B.V. The interdependence between electricity and natural gas systems has lately increased due to the wide deployment of gas-fired power plants (GFPPs). Moreover, weather-driven renewables introduce uncertainty in the operation of the integrated energy system, increasing the need for operational flexibility. Recently proposed stochastic dispatch models optimally use the available flexibility and minimize the total expected system cost. However, these models are incompatible with the current sequential market design. We propose a novel method to optimally define the available natural gas volume for power production scheduling, anticipating the real-time flexibility needs. This volume-based model is formulated as a stochastic bilevel program that aims to enhance the inter-temporal coordination of scheduling and balancing operations, while remaining compatible with the sequential clearing of day-ahead and real-time markets. The proposed model accounts for the inherent flexibility of the natural gas system via the proper modeling of linepack capabilities and reduces the total expected system cost by the optimal definition of natural gas volume availability for GFPPs at the forward phase. The volume-based coordination model is compared with a price-based coordination alternative, which was recently proposed. In the latter one, the natural gas price perceived by GFPPs is similarly adjusted to enhance the temporal coordination of scheduling and balancing stages. This comparison enables us to highlight the main properties and differences between the two coordination mechanisms.
  • Supplier default dependencies
    Item type: Journal Article
    Wagner, Stephan M.; Bode, Christoph; Koziol, Philipp (2009)
    European Journal of Operational Research
  • Share functions for cooperative games with levels structure of cooperation
    Item type: Journal Article
    Alvarez-Mozos, M.; Brink, R. van den; Laan, G. van der; et al. (2013)
    European Journal of Operational Research
  • A novel model for transfer synchronization in transit networks and a Lagrangian-based heuristic solution method
    Item type: Journal Article
    Ansarilari, Zahra; Bodur, Merve; Shalaby, Amer (2024)
    European Journal of Operational Research
    To realize the benefits of network connectivity in transfer-based transit networks, it is critical to minimize transfer disutility for passengers by synchronizing timetables of intersecting routes. We propose a mixed-integer linear programming timetable synchronization model that incorporates new features, such as dwell time determination and vehicle capacity consideration, which have been largely overlooked in the literature at the scheduling stage. We introduce a new concept of pre-planned holding time, called transfer buffer time, to reduce the transfer waiting time, particularly for transfers to low-frequency routes, while taking into account the penalty of extra in-vehicle time for onboard passengers and the possible consequences on headway regularity of a route. We develop a Lagrangian relaxation-based heuristic to obtain high-quality solutions efficiently for large instances. Our experiments on instances with up to 12 transfer nodes in the City of Toronto, with a mixture of low- and high-frequency routes, illustrate the potential benefits of the proposed model over the state of the art. The results indicate that incorporating transfer buffer time, dwell time determination, and vehicle capacity consideration improves model outcomes considerably, also demonstrating the computational efficiency of our Lagrangian-based solution method.
  • An exact approach for the multi-depot electric bus scheduling problem with time windows
    Item type: Journal Article
    Gkiotsalitis, Konstantinos; Iliopoulou, Christina; Kepaptsoglou, Konstantinos L. (2023)
    European Journal of Operational Research
    This study extends the multi-depot vehicle scheduling problem with time windows (MDVSPTW) to the case of electric vehicles which can recharge at charging stations located at any point of the service operation area. We propose a mixed-integer nonlinear model for the electric bus multi-depot vehicle scheduling problem with time windows (EB-MDVSPTW). Our formulation considers not only the operational cost of vehicles, but also the waiting times. In addition, it explicitly considers the capacity of charging stations and prohibits the simultaneous charging of different vehicles at the same charger. Chargers are modeled as task nodes of an extended network and can be placed at any location utilizing the charging infrastructure of a city instead of using only bus-dedicated chargers. Further, we linearize the MINLP formulation of the EB-MDVSPTW by reformulating it to a mixed-integer linear program (MILP) that can be solved to global optimality. Because EB-MDVSPTW is NP-Hard, we also introduce valid inequalities to tighten the search space of the MILP and we investigate the trade-off between the compactness and the tightness of the problem in benchmark instances with up to 30 trips. In the numerical experiments, we show that the valid inequalities reduce the problem’s compactness by increasing up to three times the number of constraints, but, at the same time, improve tightness resulting in computational time improvements of up to 73% in 20-trip instances. The implementation of our exact approach is demonstrated in a toy network and in the benchmark instances of Carpaneto et al. (1989).
  • Interpretable generalized additive neural networks
    Item type: Journal Article
    Kraus, Mathias; Tschernutter, Daniel; Weinzierl, Sven; et al. (2024)
    European Journal of Operational Research
    We propose Interpretable Generalized Additive Neural Networks (IGANN), a novel machine learning model that uses gradient boosting and tailored neural networks to obtain high predictive performance while being interpretable to humans. We derive an efficient training algorithm based on the theory of extreme learning machines, that allows reducing the training process to solving a sequence of regularized linear regressions. We analyze the algorithm theoretically, provide insights into the rate of change of so-called shape functions, and show that the computational complexity of the training process scales linearly with the number of samples in the training dataset. We implement IGANN in PyTorch, which allows the model to be trained on graphics processing units (GPUs) to speed up training. We demonstrate favorable results in a variety of numerical experiments and showcase IGANN's value in three real-world case studies for productivity prediction, credit scoring, and criminal recidivism prediction.
  • Organizational vulnerability of digital threats: A first validation of an assessment method
    Item type: Journal Article
    Scholz, Roland W.; Czichos, Reiner; Parycek, Peter; et al. (2020)
    European Journal of Operational Research
    We present a Strengths, Vulnerability, and Intervention Assessment related to Digital Threats (SVIDT) method, which provides a problem structuring and decision support for organizational vulnerability and resilience management with respect to changes of the digital transition. The method starts from (i) a multi-level actor analysis, (ii) identifies strengths and weaknesses of organizations, (iii) constructs digital threat scenarios and provides judgment-based expert assessments on the organization's vulnerability, (iv) develops intervention scenarios for tangible threat scenarios, and (v) suggests win-win action scenarios when referring to the multi actor system analysis as for strategic management. A first validation and application includes a structural analysis of the response patterns and a quantitative and qualitative appraisal of the organizations’ managers. This validation is based on an application of the method to 18 German and Austrian organizations of different types and magnitude. We show how the basic concepts of vulnerability (i.e., sensitivity, exposure adaptive capacity) can be quantitatively operationalized when constructing consistent combinations of threat and intervention scenarios. The validation approaches indicate that the method provides meaningful data and assessments and that the managers provided a positive feedback on the method and the recommendations which they received. It is further deliberated whether the assessment method supports organizations’ specified resilience management in an overly complex, systemic digital transition in a (semi) quantitative manner. In addition, we discuss needs for future research regarding practical utility of SVIDT, as well as the positioning of SVIDT in relation to soft operational methods and other methods of operational research.
  • Modeling soft unloading constraints in the multi-drop container loading problem
    Item type: Journal Article
    Bonet Filella, Guillem; Trivella, Alessio; Corman, Francesco (2023)
    European Journal of Operational Research
    The multi-drop container loading problem (MDCLP) requires loading a truck so that boxes can be unloaded at each drop-off point without rearranging other boxes to deliver later. However, modeling such unloading constraints as hard constraints, as done in the literature, limits the flexibility to optimize the packing and utilize the vehicle capacity. We instead propose a more general approach that considers soft unloading constraints. Specifically, we penalize unnecessary relocations of boxes using penalty functions that depend on the volume and weight of the boxes to move as well as the type of move. Our goal is to maximize the value of the loaded cargo including penalties due to violations of the unloading constraints. We provide a mixed-integer linear programming formulation for the MDCLP with soft unloading constraints, which can solve to optimality small-scale instances but is intractable for larger ones. We thus propose a heuristic framework based on a randomized extreme-point constructive phase and a subsequent improvement phase. The latter phase iteratively destroys regions in the packing space where high penalties originate, and reconstructs them. Extensive numerical experiments involving different instances and penalties highlight the advantages of our method compared to a commercial optimization solver and a heuristic from the literature developed for a related problem. They also show that our approach significantly outperforms: (i) the hard unloading constraints approach, and (ii) a sequential heuristic that neglects unloading constraints first and evaluates the penalties afterwards. Our findings underscore the relevance of accounting for soft unloading constraints in the MDCLP.
  • Scheduling periodic customer visits for a travelling salesperson
    Item type: Journal Article
    Doerner, Karl F.; Hartl, Richard F.; Kiechle, Günter; et al. (2007)
    European Journal of Operational Research
Publications 1 - 10 of 51