Hierarchical adaptive Multi-objective resource management for many-core systems

2019 ◽  
Vol 97 ◽  
pp. 416-427 ◽  
Author(s):  
André Luís del Mestre Martins ◽  
Alzemiro Henrique Lucas da Silva ◽  
Amir M. Rahmani ◽  
Nikil Dutt ◽  
Fernando Gehm Moraes
Keyword(s):  
Resource Management ◽  
Multi Objective ◽  
Many Core

Dark Silicon Aware Resource Management for Many-Core Systems

2018 ◽  
pp. 127-170 ◽  
Author(s):  
Heba Khdr ◽  
Santiago Pagani ◽  
Muhammad Shafique ◽  
Jörg Henkel
Keyword(s):  
Resource Management ◽  
Dark Silicon ◽  
Many Core

scholarly journals Performance evaluation of elitist-mutated multi-objective particle swarm optimization for integrated water resources management

2009 ◽  
Vol 11 (1) ◽  
pp. 79-88 ◽  
Author(s):  
M. Janga Reddy ◽  
D. Nagesh Kumar
Keyword(s):  
Decision Making ◽  
Particle Swarm Optimization ◽  
Resource Management ◽  
Water Resources ◽  
Water Resource Management ◽  
Pareto Optimal ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Swarm Optimization ◽  
Multi Objective

Optimal allocation of water resources for various stakeholders often involves considerable complexity with several conflicting goals, which often leads to multi-objective optimization. In aid of effective decision-making to the water managers, apart from developing effective multi-objective mathematical models, there is a greater necessity of providing efficient Pareto optimal solutions to the real world problems. This study proposes a swarm-intelligence-based multi-objective technique, namely the elitist-mutated multi-objective particle swarm optimization technique (EM-MOPSO), for arriving at efficient Pareto optimal solutions to the multi-objective water resource management problems. The EM-MOPSO technique is applied to a case study of the multi-objective reservoir operation problem. The model performance is evaluated by comparing with results of a non-dominated sorting genetic algorithm (NSGA-II) model, and it is found that the EM-MOPSO method results in better performance. The developed method can be used as an effective aid for multi-objective decision-making in integrated water resource management.

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