Search results for "Modeling and simulation"
showing 10 items of 1561 documents
Scheduling in a continuous galvanizing line
2009
In this paper we address a sequencing problem in a Continuous Galvanizing Line of a Spanish Steel Company. Production scheduling in this context is an extremely complex task which needs to take into account many constraints. We present a conceptually simple model and a Tabu Search (TS) algorithm that efficiently solves it. The TS moves are defined in order to repair non-satisfied constraints, leading to smaller and more efficient neighbourhoods. The TS co-ordinates several intensification and diversification procedures guided by an evaluation function based on a shifting penalty strategy. This function reinforces the anticycling mechanism and makes the algorithm avoid already visited soluti…
GRASP and path relinking for the equitable dispersion problem
2013
The equitable dispersion problem consists in selecting a subset of elements from a given set in such a way that a measure of dispersion is maximized. In particular, we target the Max-Mean dispersion model in which the average distance between the selected elements is maximized. We first review previous methods and mathematical formulations for this and related dispersion problems and then propose a GRASP with a Path Relinking in which the local search is based on the Variable Neighborhood methodology. Our method is specially suited for instances in which the distances represent affinity and are not restricted to take non-negative values. The computational experience with 120 instances shows…
Variable neighborhood search for the linear ordering problem
2006
Given a matrix of weights, the linear ordering problem (LOP) consists of finding a permutation of the columns and rows in order to maximize the sum of the weights in the upper triangle. This NP-complete problem can also be formulated in terms of graphs, as finding an acyclic tournament with a maximal sum of arc weights in a complete weighted graph. In this paper, we first review the previous methods for the LOP and then propose a heuristic algorithm based on the variable neighborhood search (VNS) methodology. The method combines different neighborhoods for an efficient exploration of the search space. We explore different search strategies and propose a hybrid method in which the VNS is cou…
Adaptive memory programming for constrained global optimization
2010
The problem of finding a global optimum of a constrained multimodal function has been the subject of intensive study in recent years. Several effective global optimization algorithms for constrained problems have been developed; among them, the multi-start procedures discussed in Ugray et al. [1] are the most effective. We present some new multi-start methods based on the framework of adaptive memory programming (AMP), which involve memory structures that are superimposed on a local optimizer. Computational comparisons involving widely used gradient-based local solvers, such as Conopt and OQNLP, are performed on a testbed of 41 problems that have been used to calibrate the performance of su…
A fast 3D dual boundary element method based on hierarchical matrices
2008
AbstractIn this paper a fast solver for three-dimensional BEM and DBEM is developed. The technique is based on the use of hierarchical matrices for the representation of the collocation matrix and uses a preconditioned GMRES for the solution of the algebraic system of equations. The preconditioner is built exploiting the hierarchical arithmetic and taking full advantage of the hierarchical format. Special algorithms are developed to deal with crack problems within the context of DBEM. The structure of DBEM matrices has been efficiently exploited and it has been demonstrated that, since the cracks form only small parts of the whole structure, the use of hierarchical matrices can be particula…
Cross-entropy-based adaptive optimization of simulation parameters for Markovian-driven service systems
2005
Abstract Markov fluid models represent a general description of the process of service request arrivals to service systems. The solution of performance analysis problems incorporating them often calls for a simulation approach, for which a reference methodology is Importance Sampling. However, in this case the appropriate choice of the biasing conditions is a problem in itself. In this paper an iterative method based on the cross-entropy is proposed for this choice. The equations are given that allow to derive the biasing conditions from the simulation itself. The application of the proposed method to three different sample cases, referring to one transient scenario (finite time horizon and…
An approximate fixed point result for multivalued mappings under two constraint inequalities
2017
We consider an approximate multivalued fixed point problem under two constraint inequalities, for which we provide sufficient conditions for the existence of at least one solution. Then, we present some consequences and related results.
An exact algorithm for the fuzzy p-median problem
1999
In this paper we propose a fuzzy version of the classical p-median problem. We consider a fuzzy set of constraints so that the decision-maker will be able to take into account solutions which provide significantly lower costs by leaving a part of the demand uncovered. We propose an algorithm for solving the problem which is based on Hakimi's works and we compare the crisp and the fuzzy approach by means of an example.
On the equivalence of two optimization methods for fuzzy linear programming problems
2000
Abstract The paper analyses the linear programming problem with fuzzy coefficients in the objective function. The set of nondominated (ND) solutions with respect to an assumed fuzzy preference relation, according to Orlovsky's concept, is supposed to be the solution of the problem. Special attention is paid to unfuzzy nondominated (UND) solutions (the solutions which are nondominated to the degree one). The main results of the paper are sufficient conditions on a fuzzy preference relation allowing to reduce the problem of determining UND solutions to that of determining the optimal solutions of a classical linear programming problem. These solutions can thus be determined by means of classi…
Viability of infeasible portfolio selection problems: A fuzzy approach
2002
Abstract This paper deals with fuzzy optimization schemes for managing a portfolio in the framework of risk–return trade-off. Different models coexist to select the best portfolio according to their respective objective functions and many of them are linearly constrained. We are concerned with the infeasible instances of such models. This infeasibility, usually provoked by the conflict between the desired return and the diversification requirements proposed by the investor, can be satisfactorily avoided by using fuzzy linear programming techniques. We propose an algorithm to repair infeasibility and we illustrate its performance on a numerical example.