Archive for: ‘May 2014’

Implementation of MATLAB Quadprog in Meshless Methods

May 18, 2014 Posted by admin

Khadija Khammari and Hicham Fihri Fassi

LERMO, Faculty of Sciences and Technology, Hassan1er University
Box 577 road of Casablanca, Settat, 26000, Morocco

Abstract
This paper deals with the numerical implementation of the Element-free Galerkin method to solve two dimensional elasto-static problems using the Moving Least Squares (MLS) approximation. The Galerkin weak form is employed to obtain a system of equations, and the Lagrange multipliers method is applied for imposing the boundary conditions. The system of equations is solved using the matrix and the mathematical programming methods. Numerical examples/cases are given to test the efficiency of both methods .However our interest and attention are focused more on investigating whether the second method is more suitable for solving non-linear problems.

Keywords:EFG method, MLS approximation, elasticity, Lagrange multipliers, mathematical programming.

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Comparison of Evolutionary and Swarm Intelligence-based Approaches in the Improvement of Peach Fruit Quality

May 18, 2014 Posted by admin

A. Kadrani, B. Quilot-Turion, M. Génard, F. Lescourret and
M-M. Ould Sidi

INSEA, BP 6217 Rabat-Institus, 10106 Rabat, Maro
INRA, UR1052 Génétique et Amélioration des Fruits et Légumes, F-84143 Montfavet, France
INRA, R1115 Plantes et Systèmes de culture Horticoles, F-84914 Avignon, France

Abstract
The design of peach ideotypes that satisfy the requirement of high fruit quality and low sensitivity to fungal diseases in a given environment is a very challenging problem. In this paper, we propose a model-based design approach to deal with this challenge. First, we formulate it as a multi-objective optimization problem. Two well-known multi-objective optimization algorithms i.e. the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and the Multi-Objective Particle Swarm Optimization with the Crowding Distance (MOPSO-CD) were then used to find the best combinations of genetic resources and cultural practices adapted to, and respectful of specific environments. Statistically significant performance measures are employed to compare the two algorithms. The results obtained demonstrate that NSGA-II is able to yield a wide spread of solutions with good coverage and convergence to Pareto fronts.

Keywords:Multi-objective optimization, NSGA-II, MOPSO-CD, decision-making, model-based design, peach ideotypes, brown rot, Virtual Fruit model.

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Multicriteria Decision Making: A Case Study in the Automobile Industry

May 18, 2014 Posted by admin

Márcia Oliveira, Dalila B. M. M. Fontes and Teresa Pereira
FEP, Faculdade de Economia da Universidade do Porto, and LIAAD/INESC TEC, Rua Dr. Roberto Frias, 4200-464 Porto, Portugal
IPP/ESEIG, Escola Superior de Estudos Industriais e de Gestão, Instituto Politécnico do Porto, CIEFGEI, Rua D. Sancho I, 981, 4480-876, Vila do Conde, Portugal and Algoritmi Center, Universidade do Minho, 4800-058 Guimarães, Portugal

Abstract
Multicriteria decision analysis (MCDA) has been one of the fastest-growing areas of operations research during the last decade. The research attention devoted to MCDA motivated the development of a great variety of approaches and methods within the field. These methods differentiate themselves in terms of procedures, theoretical assumptions and type of decision addressed. This diverseness of these methods poses a great challenge to the process of selecting the most suitable method for a specific real-world decision problem. In this paper, we present a case study for a real-world decision problem in the painting department of an automobile assembly plant. We solved the problem by applying the well-known AHP method and the MCDA method proposed by Pereira and Sameiro de Carvalho (2005) (MMASSI). By applying two MCDA methods rather than one, we expect to improve the robustness of the results obtained. The contributions of this paper are twofold: first, we intend to compare the results obtained with the two MCDA methods (i.e. AHP and MMASSI). Secondly, we intend to enrich the literature in the field with a real-world MCDA case study on a complex decision making problem, since there is a paucity of research work addressing real-world decision problems faced by organizations.

Keywords:AHP, decision making, multicriteria decision analysis, multicriteria methodology, automobile industry.

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A Hybrid Approach for Milk Collection Using Trucks and Trailers

May 18, 2014 Posted by admin

Urooj Pasha, Arild Hoff and Arne Løkketangen
Molde University College, P.O.Box 2110, NO-6402 Molde, Norway Arne Løkketangen passed away June 10th 2013

Abstract
Collection and transportation of milk from farms to production factories is a crucial issue around the world. This problem can often be seen as a special case of the Truck and Trailer Vehicle Routing Problem (TTVRP) in which a trailer cannot be driven along with a truck to the farms and must be parked in the nearest available parking place while the truck visits farms and collects milk. Then, the truck returns to the parking place, transfers milk to the trailer and starts a new sub route or continues the route with the trailer. The collections, transportation, and distribution operations in TINE SA, a leading dairy company in Norway, is a typical example of this problem. In this paper, we solve a real world planning and distribution problem for the company (TINE SA). A method involving a clustering technique followed by a heuristic based on tabu search is developed to solve this problem. The proposed method is able to find a cost-effective solution by using natural geographical clusters and choosing vehicle types that fit better to the farms production and the dairy plants demand. The new suggested solution produces a more suitable vehicle mix and collecting frequency, a better utilization of vehicles and smaller variable costs than the current route structure of the company.

Keywords: vehicle routing, tabu search, clustering

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Weight Stability Intervals in Multicriteria Decision Aid Under Semiorder Preference Structures

May 18, 2014 Posted by admin

Gabriela Fernández Barberis and M del Carmen Escribano Ródenas
University of Campinas (UNICAMP), 13083-859 Campinas – SP, Brazil Department of Computational and Applied Mathematics,Rice University Houston Texas, U.S.A.

Abstract
One essential problem in Multicriteria Decision Aid is to assess the relative importance of different criteria. The use of weights gives the decision-maker the possibility to better modelize the real aspects of a decision problem and to express more freedom the preference structure he has in his mind. This task is not easy because a subjective component is always present and there exist great number of methods which try to approximate this problem. PROMETHEE Methods consider as outranking non-compensatory methods; give the possibility to calculate weight stability intervals. So it is very important to do sensibility analysis taking into account that changes in weights would be reflected in PROMETHEE decision axis and they could affect previous conclusions. The idea of weight stability intervals (WSI) was introduced by Mareschal (1988) in PROMETHEE Methods. It is well known that these methods work under a preorder preference structure, so we propose to calculate the WSI under a semiorder structure with the aim to study the stability and the robustness of the model from a more solid point of view. In this paper we propose to analyze in a first-order additive method, to say, with only one valued real function, specifically in PROMETHEE II, the sensibility of a Semiorder Preference Structure under changes in the weight vector. The task consists of defining New Weight Stability Intervals (NWSI) adapted to a Semiorder Preference Structure in PROMETHEE Methods.

Keywords: weight stability interval, semiorder preference structure, PROMETHEE Methods, thresholds.

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Computing a hybrid preconditioner approach to solve the linear systems arising from interior point methods for linear programming using the conjugate gradient method

May 18, 2014 Posted by admin

Carla T. L. S. Ghidini, A. R. L. Oliveira and D. C. Sorensen
University of Campinas (UNICAMP), 13083-859 Campinas – SP, Brazil Department of Computational and Applied Mathematics,Rice University Houston Texas, U.S.A.

Abstract
In this work, iterative methods are used to solve the linear systems of equations arising from interior point methods. Since these systems of equations are very ill-conditioned near a solution, the design of specially tailored preconditioners is an important implementation issue. On the other hand, the early linear systems of equations do not present the same features and it is advisable to adopt hybrid preconditioners that begin as a generic preconditioner and adapt during the course of the iteration, becoming ever more specialized as convergence takes place. During the initial iterations, a controlled Cholesky factorization is used. As convergence takes place, a splitting, the splitting preconditioner is adopted. Its major advantage is its excellent behavior near a solution of the linear program. This desirable feature has a price. The preconditioner could be very expensive to compute. A careful implementation must be performed in order to achieve competitive results regarding both: speed and robustness. An effective implementation of the splitting preconditioner relies upon finding a suitable set of linearly independent columns to form a nonsingular matrix from the constraint matrix. Several strategies to help finding such set of columns are presented. Numerical experiments are carried out in order to illustrate the performance of the given strategies.

Keywords: linear programming, interior point methods, preconditioning.

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Two Multiobjective Metaheuristics for Solving the Integrated Problem of Frequencies Calculation and Departures Planning in an Urban Transport System

May 18, 2014 Posted by admin

Paulina A. Avila Torres* and Fernando López Irarragorri
Universidad Autónoma de Nuevo León, Graduate Program in Systems Engineering, San Nicolás de los Garza 66451, México.

Abstract
The process of urban public transport planning commonly includes four basic activities, usually executed in sequence: Network design, Timetabling, Vehicle scheduling and Crew scheduling. In this paper we present a multiobjective model that integrates the calculation of minimum frequencies and departures scheduling (minimum frequencies are calculated when solving the Network Design Problem. The calculated frequencies are employed for Timetabling Construction Problem). Two multiobjective metaheuristics for solving randomly generated instances of the problem are presented and their performances are compared. The main scientific contribution of this paper is the development of an integrated mixed integer linear programming model to construct timetable by selecting frequencies in such a way that multiple objectives, like operational cost, synchronization, transfer time and smooth transitions between periods are optimized.

Keywords: Integrated, frequency, timetable.

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Ranking of the Lithuanian Banks During the Recession of 2008-2009 by the MULTIMOORA Method

May 18, 2014 Posted by admin

Willem Karel M. Brauers, Romualdas Ginevicius and Askoldas Podvezko
Faculty of Applied Economics, University of Antwerp, Prinsstraat, 13, 2600, Antwerpen Belgium and Vilnius Gediminas Technical University, Lithuania,Department of Enterprise Economics and Business Management, Vilnius Gediminas Technical University, Saulėtekio al. 11, LT, 10223, Vilnius, Lithuania,

Abstract
The aim of this study is to do a critical analysis, on the basis of different objectives, the banks registered in Lithuania during the recession years 2008-2009. As these banks work in the same macro-economic environment, the objectives are chosen on the basis of the CAMEL classification (‘C’ Capital adequacy, ‘A’ Asset quality, ‘M’ Management quality, ‘E’ Earnings, ‘L’ Liquidity). Traditional Cost-Benefit Analysis is not suitable enough for this. Indeed Cost-Benefit analysis translates all direct and indirect costs and other objectives (benefits) into money terms. On the contrary, Multi-Objective Optimization takes care of the different objectives, with objectives keeping their own units. Different methods exist for the application of Multi-Objective Optimization. In our research, we tested these methods for their robustness. MOORA (Multi-Objective Optimization by Ratio analysis) and MULTIMOORA (MOORA plus a Full Multiplicative Form), showed positive results on these tests. Therefore MULTIMOORA was chosen for the ranking of the Lithuanian Banks during the recession years 2008-2009.

Keywords: Multi-objective optimization, Lithuanian banks, bank objectives, robustness, ratio system, Reference point method, Full multiplicative form.

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  • Annals of Management Science (AMS)

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  • ISSN 2161-5012 (Print Version)
    ISSN 2161-5004 (Online Version)