Sensitivity analysis for variational inequalities defined on polyhedral sets
Mathematics of Operations Research
Annals of Operations Research - Special issue on hierarchical optimization
Interactive balance space approach for solving multi-level multi-objective programming problems
Information Sciences: an International Journal
Comparative tests of solution methods for signal-controlled road networks
Information Sciences: an International Journal
Networked H∞ control of linear systems with state quantization
Information Sciences: an International Journal
Quantized output feedback control for networked control systems
Information Sciences: an International Journal
Optimization of limited network capacity with toll settings
Information Sciences: an International Journal
On bilevel multi-follower decision making: General framework and solutions
Information Sciences: an International Journal
Model, solution concept, and Kth-best algorithm for linear trilevel programming
Information Sciences: an International Journal
Optimization of a nonlinear area traffic control system with elastic demand
Automatica (Journal of IFAC)
Tabu assisted guided local search approaches for freight service network design
Information Sciences: an International Journal
Estimation of distribution algorithm for a class of nonlinear bilevel programming problems
Information Sciences: an International Journal
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This paper proposes a bi-level programming for a logistics network design problem with system-optimized flows. We applied the Wardrop's second principle to the logistics network design problem. A system-optimized logistics network design problem can be formulated as a bi-level program. For the system-optimized flows, a user equilibrium traffic assignment problem with marginal costs can be solved at the lower level problem. Due to the non-differentiability of the perturbed solutions in system-optimized flows, we present a novel solution algorithm to efficiently solve the logistics network design problem. By using the subgradients of the objective function, a new projection method is proposed with global convergence. Numerical calculations are implemented using a grid-size hypothetical network and comparisons are made with other alternatives in solving the logistics network design problem. Numerical results disclose that the proposed method has successful solved the logistics network design problem and achieved significant performance both in computational efficacy and cost reduction when compared to other alternatives.