Search results for " optimization"
showing 10 items of 2367 documents
Considering safety issues in minimum losses reconfiguration for MV distribution networks
2009
This paper offers a new perspective over the traditional problem of the multiobjective optimal reconfiguration of electrical distribution systems in regular working state. The issue is indeed here formulated including also safety issues. Indeed, dimensioning the earth electrodes of their own secondary substations, distribution companies take into account the probable future configurations of the network due to transformations of overhead lines into cable lines or realization of new lines. On the contrary, they do not consider that, during normal working conditions. the structure of the network can be modified for long periods as a consequence of reconfiguration manoeuvres, with differences …
On determining unknown functions in differential systems, with an application to biological reactors.
2003
In this paper, we consider general nonlinear systems with observations, containing a (single) unknown function φ . We study the possibility to learn about this unknown function via the observations: if it is possible to determine the [values of the] unknown function from any experiment [on the set of states visited during the experiment], and for any arbitrary input function, on any time interval, we say that the system is “identifiable”. For systems without controls, we give a more or less complete picture of what happens for this identifiability property. This picture is very similar to the picture of the “observation theory” in [7]: Contrarily to the case of the observability property, i…
Multi-modal search for multiobjective optimization: an application to optimal smart grids management
2012
This paper studies the possibility to use efficient multimodal optimizers for multi-objective optimization. In this paper, the application area considered for such new approach is the optimal dispatch of energy sources in smart microgrids. The problem indeed shows a non uniform Pareto front and requires efficient optimal search methods. The idea is to exploit the potential of agents in population-based heuristics to improve diversity in the Pareto front, where solutions show the same rank and are thus equally weighted. Since Pareto dominance is at the basis of the theory of multi-objective optimization, most algorithms show the non dominance ranking as quality indicator, with some problem i…
Scatter search for an uncapacitated p-hub median problem
2015
Scatter search is a population-based method that has been shown to yield high-quality outcomes for combinatorial optimization problems. It uses strategies for combining solution vectors that have proved effective in a variety of problem settings. In this paper, we present a scatter search implementation for an NP -hard variant of the classic p-hub median problem. Specifically, we tackle the uncapacitated r-allocation p-hub median problem, which consists of minimizing the cost of transporting the traffics between nodes of a network through special facilities that act as transshipment points. This problem has a significant number of applications in practice, such as the design of transportati…
A hybrid evolution strategy for the open vehicle routing problem
2010
This paper presents a hybrid evolution strategy (ES) for solving the open vehicle routing problem (OVRP), which is a well-known combinatorial optimization problem that addresses the service of a set of customers using a homogeneous fleet of non-depot returning capacitated vehicles. The objective is to minimize the fleet size and the distance traveled. The proposed solution method manipulates a population of @m individuals using a (@m+@l)-ES; at each generation, a new intermediate population of @l offspring is produced via mutation, using arcs extracted from parent individuals. The selection and combination of arcs is dictated by a vector of strategy parameters. A multi-parent recombination …
A two-point boundary value formulation of a mean-field crowd-averse game
2014
Abstract We consider a population of “crowd-averse” dynamic agents controlling their states towards regions of low density. This represents a typical dissensus behavior in opinion dynamics. Assuming a quadratic density distribution, we first introduce a mean-field game formulation of the problem, and then we turn the game into a two-point boundary value problem. Such a result has a value in that it turns a set of coupled partial differential equations into ordinary differential equations.
Scheduling a cellular manufacturing system with GA
2002
The flexible manufacturing cell scheduling problem is considered with a multi-objective approach, pursuing together makespan minimisation and the in process job wait minimisation. The formulation of the scheduling problem is discussed, analysing how to generate well suited sequences, like generalised permutation sequences, and the proper construction of a JIT timing of activities. An evolutionary sequencing algorithm based on both classic genetic operators and hybrid operators is then proposed. The hybrid operators have been introduced to construct highly fit initial population, to perform periodically a local search on the population and to maintain enough genetical diversity in the actual…
A hybrid genetic algorithm with local search
2001
Abstract A hybrid genetic algorithm with internal local search was developed for optimisations involving continuous variables. The reproduction probabilities were enhanced using the fitness values obtained when a local method was applied to each individual in the population. These estimations are more realistic, since consider not the apparent but the hidden, latent quality of each individual. The information gathered in the local search was also used to build an auxiliary population recording the successfully enhanced individuals, which allowed to detect the convergence and self-adapt the search limits. The size of this auxiliary population was kept constant by a cluster analysis strategy.…
Opinion dynamics and stubbornness through mean-field games
2013
This paper provides a mean field game theoretic interpretation of opinion dynamics and stubbornness. The model describes a crowd-seeking homogeneous population of agents, under the influence of one stubborn agent. The game takes on the form of two partial differential equations, the Hamilton-Jacobi-Bellman equation and the Kolmogorov-Fokker-Planck equation for the individual optimal response and the population evolution, respectively. For the game of interest, we establish a mean field equilibrium where all agents reach epsilon-consensus in a neighborhood of the stubborn agent's opinion.
A Population-Based Approach to the Resource-Constrained Project Scheduling Problem
2004
We present a population-based approach to the RCPSP. The procedure has two phases. The first phase handles the initial construction of a population of schedules and these are then evolved until high quality solutions are obtained. The evolution of the population is driven by the alternative application of an efficient improving procedure for locally improving the use of resources, and a mechanism for combining schedules that blends scatter search and path relinking characteristics. The objective of the second phase is to explore in depth those vicinities near the high quality schedules. Computational experiments on the standard j120 set, generated using ProGen, show that our algorithm produ…