Sensitivity analysis for variational inequalities defined on polyhedral sets
Mathematics of Operations Research
A nonsmooth version of Newton's method
Mathematical Programming: Series A and B
Design of robust active queue management controllers for a class of TCP communication networks
Information Sciences: an International Journal
Comparative tests of solution methods for signal-controlled road networks
Information Sciences: an International Journal
A non-smooth optimization model for a two-tiered supply chain network
Information Sciences: an International Journal
Networked H∞ control of linear systems with state quantization
Information Sciences: an International Journal
Performance enhancement of TCP in high-speed networks
Information Sciences: an International Journal
Compensation for control packet dropout in networked control systems
Information Sciences: an International Journal
Quantized output feedback control for networked control systems
Information Sciences: an International Journal
Improving fairness among TCP flows by stateless buffer control with early drop maximum
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
Hybrid optimization with improved tabu search
Applied Soft Computing
Structural-acoustic optimization of a rectangular plate: A tabu search approach
Finite Elements in Analysis and Design
Information Sciences: an International Journal
| Hi-index | 0.07 |
Consider a road network with severe traffic congestion. A set of efficient strategies can be addressed to simultaneously minimize road users' travel times and maximize possible increase in travel demands. Due to the non-differentiability of the perturbed solutions in equilibrium constraints, non-smooth optimization models for delay-minimizing and capacity-maximizing signal setting problems are established. In this paper, we propose a new bundle subgradient projection approach to solve the signal setting problems with global convergence. Various control policies are numerically tested one against another. Numerical results disclose that the proposed approach has successfully solved the delay-minimizing and capacity maximizing signal setting problems and achieved significant performance in cost reduction when compared to other alternatives.