Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Discrete optimization
Knapsack problems: algorithms and computer implementations
Knapsack problems: algorithms and computer implementations
Network programming
Tabu Search
Dynamic Programming and Strong Bounds for the 0-1 Knapsack Problem
Management Science
Multi-period design of survivable wireless access networks under capacity constraints
Decision Support Systems
On the design problem of cellular wireless networks
Wireless Networks - Special issue: Selected papers from ACM MobiCom 2003
International Journal of Network Management
Design of IEEE 802.16-based multi-hop wireless backhaul networks
AcessNets '06 Proceedings of the 1st international conference on Access networks
Metaheuristics for optimization problems in computer communications
Computer Communications
Survivable and delay-guaranteed backbone wireless mesh network design
Journal of Parallel and Distributed Computing
Information Assurance: Dependability and Security in Networked Systems
Information Assurance: Dependability and Security in Networked Systems
An efficient link allocation algorithm for survivable ATM-based personal communication networks
Computers and Operations Research
Heuristic algorithms for designing minimum cost FSO networks
ANTS'09 Proceedings of the 3rd international conference on Advanced networks and telecommunication systems
A tabu search approach for assigning cells to switches in cellular mobile networks
Computer Communications
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This paper presents a new heuristic algorithm for designing least-cost telecommunications networks to carry cell site traffic to wireless switches while meeting survivability, capacity, and technical compatibility constraints. This requires solving the following combinatorial optimization problems simultaneously: (1) Select a least-cost subset of locations (network nodes) as hubs where traffic is to be aggregated and switched, and choose the type of hub (high-capacity DS3 vs. lower-capacity DS1 hub) for each location; (2) Optimally assign traffic from other nodes to these hubs, so that the traffic entering the network at these nodes is routed to the assigned hubs while respecting capacity constraints on the links and routing-diversity constraints on the hubs to assure survivability; and\break (3) Optimally choose the types of links to be used in interconnecting the nodes and hubs based on the capacities and costs associated with each link type. Each of these optimization problems must be solved while accounting for its impacts on the other two. This paper introduces a short term Tabu Search (STTS) meta-heuristic, with embedded knapsack and network flow sub-problems, that has proved highly effective in designing such “backhaul networks” for carrying personal communications services (PCS) traffic. It solves problems that are challenging for conventional branch-and-bound solvers in minutes instead of hours and finds lower-cost solutions. Applied to real-world network design problems, the heuristic has successfully identified designs that save over 20% compared to the best previously known designs.