A new algorithm to compute pareto-optimal paths in a multi objective fuzzy weighted network
Kumar, M Karun
A new algorithm to compute pareto-optimal paths in a multi objective fuzzy weighted network - - 50 (3) Jul-Sept 2013, 297-318p.
This paper presents a new algorithm to find the shortest path (Pareto optimal) for both single and multiple objective network optimization problem involving fuzziness in objectives or QoS (Quality of Service) parameters. Each fuzzy objective or QoS parameter on the link of a network is represented as a fuzzy number. This algorithm can compute all the Pareto Optimal paths from a selected source node to all other nodes in a network and is applicable for both cyclic and acyclic networks. Computational complexity of the algorithm is presented and compared with other algorithms. The algorithm is illustrated with single and bi-objective fuzzy network optimization problems.
Network Optimization
Shortest Path
Multiple Objectives
Quality of Service
Pareto minimum
Fuzzy Number
A new algorithm to compute pareto-optimal paths in a multi objective fuzzy weighted network - - 50 (3) Jul-Sept 2013, 297-318p.
This paper presents a new algorithm to find the shortest path (Pareto optimal) for both single and multiple objective network optimization problem involving fuzziness in objectives or QoS (Quality of Service) parameters. Each fuzzy objective or QoS parameter on the link of a network is represented as a fuzzy number. This algorithm can compute all the Pareto Optimal paths from a selected source node to all other nodes in a network and is applicable for both cyclic and acyclic networks. Computational complexity of the algorithm is presented and compared with other algorithms. The algorithm is illustrated with single and bi-objective fuzzy network optimization problems.
Network Optimization
Shortest Path
Multiple Objectives
Quality of Service
Pareto minimum
Fuzzy Number
