Search results for " set"
showing 10 items of 2095 documents
An ILS-Based Metaheuristic for the Stacker Crane Problem
2012
[EN] In this paper we propose a metaheuristic algorithm for the Stacker Crane Problem. This is an NP-hard arc routing problem whose name derives from the practical problem of operating a crane. Here we present a formulation and a lower bound for this problem and propose a metaheuristic algorithm based on the combination of a Multi-start and an Iterated Local Search procedures. Computational results on a large set of instances are presented.
A fuzzy method to repair infeasibility in linearly constrained problems
2001
Abstract In this paper we introduce a fuzzy method to deal with infeasibility in linearly constrained programs. Given an infeasible instance, we determine how much we should perturb the right-hand side coefficients in order to attain feasibility and propose a ‘feasible reformulation’ of the problem. Although we prove that our algorithm always finds such a reformulation the convenience of using it can be decided by the analyst. By this, we mean that the method also provides a simple way to compute lower bounds on the changes on every right-hand side coefficient, and if the decision maker considers that some of the magnitudes are unacceptable, he or she simply stops at this step. We think tha…
Solving a class of fuzzy linear programs by using semi-infinite programming techniques
2004
This paper deals with a class of Fuzzy Linear Programming problems characterized by the fact that the coefficients in the constraints are modeled as LR-fuzzy numbers with different shapes. Solving such problems is usually more complicated than finding a solution when all the fuzzy coefficients have the same shape. We propose a primal semi-infinite algorithm as a valuable tool for solving this class of Fuzzy Linear programs and, we illustrate it by means of several examples.
A Stochastic Soft Constraints Fuzzy Model for a Portfolio Selection Problem
2006
The financial market behavior is affected by several non-probabilistic factors such as vagueness and ambiguity. In this paper we develop a multistage stochastic soft constraints fuzzy program with recourse in order to capture both uncertainty and imprecision as well as to solve a portfolio management problem. The results we obtained confirm the studies carried out in literature addressed to integrate stochastic and possibilistic programming.
Fixed domain approaches in shape optimization problems
2012
This work is a review of results in the approximation of optimal design problems, defined in variable/unknown domains, based on associated optimization problems defined in a fixed ?hold-all? domain, including the family of all admissible open sets. The literature in this respect is very rich and we concentrate on three main approaches: penalization?regularization, finite element discretization on a fixed grid, controllability and control properties of elliptic systems. Comparison with other fixed domain approaches or, in general, with other methods in shape optimization is performed as well and several numerical examples are included.
A non dominated ranking Multi Objective Genetic Algorithm and electre method for unequal area facility layout problems
2013
The unequal area facility layout problem (UA-FLP) comprises a class of extremely difficult and widely applicable optimization problems arising in diverse areas and meeting the requirements for real-world applications. Genetic Algorithms (GAs) have recently proven their effectiveness in finding (sub) optimal solutions to many NP-hard problems such as UA-FLP. A main issue in such approach is related to the genetic encoding and to the evolutionary mechanism implemented, which must allow the efficient exploration of a wide solution space, preserving the feasibility of the solutions and ensuring the convergence towards the optimum. In addition, in realistic situations where several design issues…
Applying fuzzy Particle Swarm Optimization to Multi-unit Double Auctions
2010
Abstract In the context of Quadratic Programming Problems, we use a fuzzy Particle Swarm Optimization (PSO) algorithm to analyze a Multi-unit Double Auction (MDA) market. We give also a Linear Programming (LP) based upper bound to help the decision maker in dealing with constraints in the mathematical model. In the computational study, we evaluate our algorithm and show that it is a feasible approach for processing bids and calculating assignments.
Sufficient conditions for coincidence in ℓ1 multifacility location problems
1997
We consider the problem of finding the optimal way of locating a finite number of facilities in a finite dimensional space, in order to minimize a weighted sum of the distances between these and other pre-existent facilities which are already positioned. We study the specific case where distance is measured in the @?"1, giving a new sufficient condition for identifying groups of facilities whose position will coincide at optimality.
Fuzzy green vehicle routing problem for designing a three echelons supply chain
2020
Abstract In this study, a three-echelon fuzzy green vehicle routing problem (3E-FGVRP) is considered for designing a regional agri-food supply chain on a time horizon. To account for the variability associated with the quantities requested by customers, it is assumed that the demands are fuzzy numbers simulated by a time-dependent algorithm. Moreover, the vehicle fleet and distribution centres are considered with a defined capacity. The credibility theory of fuzzy sets is used to implement a multi-objective fuzzy chance-constrained programming model, where the total costs and carbon emissions are minimised. The resolution of the 3E-FGVRP is conducted by using a non-dominated sorting genetic…
On the checking of g-coherence of conditional probability bounds
2003
We illustrate an approach to uncertain knowledge based on lower conditional probability bounds. We exploit the coherence principle of de Finetti and a related notion of generalized coherence (g-coherence), which is equivalent to the "avoiding uniform loss" property introduced by Walley for lower and upper probabilities. Based on the additive structure of random gains, we define suitable notions of non relevant gains and of basic sets of variables. Exploiting them, the linear systems in our algorithms can work with reduced sets of variables and/or constraints. In this paper, we illustrate the notions of non relevant gain and of basic set by examining several cases of imprecise assessments d…