Now showing items 1-10 of 592
A multi-objective evaluation of the impact of the penetration of Distributed Generation
This paper proposes a methodology to consider the effects of the integration of DG on planning. Since DG has potential to defer investments in networks, the impact of DG on grid capacity is evaluated. A multi-objective ...
Hybridizing a multi-objective simulated annealing algorithm with a multi-objective evolutionary algorithm to solve a multi-objective project scheduling problem
In this paper, a multi-objective project scheduling problem is addressed. This problem considers two conflicting, priority optimization objectives for project managers. One of these objectives is to minimize the project ...
A new method for decision making in multi-objective optimization problems
(Sociedade Brasileira de Pesquisa Operacional, 2012)
Many engineering sectors are challenged by multi-objective optimization problems. Even if the idea behind these problems is simple and well established, the implementation of any procedure to solve them is not a trivial ...
Characterization of robust solutions of multi-objetive optimization models with uncertain weights: applications in a sawmill
The use of weights in multi-objective problems is one of the simplest ways to include multiple criteria in optimization models, in what is known as a weighted-sum approach. However, the solution to these models is highly ...
Distributed generation impact evaluation using a multi-objective tabu search
Distribution networks paradigm is changing currently requiring improved methodologies and tools for network analysis and planning. A relevant issue is analyzing the impact of the Distributed Generation penetration in passive ...
Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation
(Elsevier B.V. Sa, 2012-08-01)
This paper proposes a multi-objective approach to a distribution network planning process that deals with the challenges derived from the integration of Distributed Generation (DG). The proposal consists of a multi-objective ...
Meta-heuristic multi- and many-objective optimization techniques for solution of machine learning problems
Recently, multi- and many-objective meta-heuristic algorithms have received considerable attention due to their capability to solve optimization problems that require more than one fitness function. This paper presents a ...
The use of possibility theory in the definition of fuzzy Pareto-optimality
(SpringerNew YorkEUA, 2011)