Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
1
4
2008
01
01
Identifying Useful Variables for Vehicle Braking Using the Adjoint Matrix Approach to the Mahalanobis-Taguchi System
281
292
EN
Elizabeth A.
Cudney
University of Missouri – Rolla, Rolla, Missouri 65409 USA
Kioumars
Paryani
Lawrence Technological University, Southfield, Massachusetts 02139 USA
Kenneth M.
Ragsdell
University of Missouri – Rolla, Rolla, Missouri 65409 USA
The Mahalanobis Taguchi System (MTS) is a diagnosis and forecasting method for multivariate data. Mahalanobis distance (MD) is a measure based on correlations between the variables and different patterns that can be identified and analyzed with respect to a base or reference group. MTS is of interest because of its reported accuracy in forecasting small, correlated data sets. This is the type of data that is encountered with consumer vehicle ratings. MTS enables a reduction in dimensionality and the ability to develop a scale based on MD values. MTS identifies a set of useful variables from the complete data set with equivalent correlation and considerably less time and data. This paper presents the application of the Adjoint Matrix Approach to MTS for vehicle braking to identify a reduced set of useful variables in multidimensional systems.
Mahalanobis-Taguchi system (MTS),Mahalanobis distance (MD),Adjoint matrix,Pattern Recognition,Orthogonal array (OA),Signal-to-noise ratio (SN),Mahalanobis space
(reference group)
http://www.jise.ir/article_3935.html
http://www.jise.ir/article_3935_ec52a34b9c898b56a2b31d65ca64675f.pdf
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
1
4
2008
01
01
A Goal Programming Method for Finding Common Weights in DEA with an Improved Discriminating Power for Efficiency
293
303
EN
A.
Makui
Department of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran.
A.
Alinezhad
Islamic Azad University-Science & Research Branch, Tehran, Iran.
R.
Kiani Mavi
Islamic Azad University-Science & Research Branch, Tehran, Iran.
M.
Zohrehbandian
Department of Mathematics, Islamic Azad University-Karaj P.O.Box 31485-313, Karaj, Iran.
A characteristic of data envelopment analysis (DEA) is to allow individual decision making units (DMUs) to select the most advantageous weights in calculating their efficiency scores. This flexibility, on the other hand, deters the comparison among DMUs on a common base. For dealing with this difficulty and assessing all the DMUs on the same scale, this paper proposes using a multiple objective linear programming (MOLP) approach for generating a common set of weights in the DEA framework.
MOLP,Goal Programming,DEA,Efficiency,Ranking,Weight restrictions
http://www.jise.ir/article_3940.html
http://www.jise.ir/article_3940_ff49d3323ef8e6b15ade4c48d88245e5.pdf
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
1
4
2008
01
01
A New Solution for the Cyclic Multiple-Part Type Three-Machine Robotic Cell Problem based on the Particle Swarm Meta-heuristic
304
317
EN
N.
Kamalabadi
Department of Industrial Engineering, University of Kurdistan, Sanandaj, Iran
S.
Gholami
Department of Industrial Engineering, Tarbiat Modares University, Tehran, Iran
A.H.
Mirzaei
Department of Industrial Engineering, Tarbiat Modares University, Tehran, Iran
In this paper, we develop a new mathematical model for a cyclic multiple-part type threemachine robotic cell problem. In this robotic cell a robot is used for material handling. The objective is finding a part sequence to minimize the cycle time (i.e.; maximize the throughput) with assumption of known robot movement. The developed model is based on Petri nets and provides a new method to calculate cycle times by considering waiting times. It is proved that scheduling problem of a robotic cell is unary NP-complete. Achieving an optimal solution for this type of complex, large-sized problem in reasonable computational time by using traditional approaches and optimization tools is extremely difficult. In this paper we implement an algorithm based on the particle swarm optimisation (PSO) method for solving the problem. To validate the developed model and solution algorithm, various test problems are examined some of which are of small-size and some other of large-size. The computational results show that the proposed algorithm achieves optimum solutions for small sized problems, while for large-sized problems this algorithm can find suitable solutions in acceptable time.
Cyclic blocking flow-shop,Particle swarm optimisation,Robotic cell,scheduling
http://www.jise.ir/article_3941.html
http://www.jise.ir/article_3941_f312ee0f00a4b926a568f4d6e5dec465.pdf
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
1
4
2008
01
01
Machine Cell Formation Based on a New Similarity Coefficient
318
344
EN
Ibrahim H.
Garbie
Department of Mechanical Engineering, Helwan University, Helwan, Cairo, 11792, EGYPT
Hamid R.
Parsaei
Department of Industrial Engineering, University of Houston, Houston, TX, 77204, USA
Herman R.
Leep
Department of Industrial Engineering, University of Louisville, Louisville, KY, 40292, USA.
One of the designs of cellular manufacturing systems (CMS) requires that a machine population be partitioned into machine cells. Numerous methods are available for clustering machines into machine cells. One method involves using a similarity coefficient. Similarity coefficients between machines are not absolute, and they still need more attention from researchers. Although there are a number of similarity coefficients in the literature, they do not always incorporate the important properties of a similarity coefficient satisfactorily. These important properties include alternative routings, processing time, machine capacity (reliability), machine capability (flexibility), production volume, product demand, and the number of operations done on a machine. The objectives of this paper are to present a review of the literature on similarity coefficients between machines in CMS, to propose a new similarity coefficient between machines incorporating all these important properties of similarity, and to propose a machine cell heuristic approach to group machines into machine cells. An example problem is included and demonstrated in this paper.
Cellular Manufacturing,Similarity coefficients,Machine cells
http://www.jise.ir/article_3942.html
http://www.jise.ir/article_3942_d78dac81d3a5e1317b9eeca337dfc821.pdf
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
1
4
2008
01
01
Generalized Cyclic Open Shop Scheduling and a Hybrid Algorithm
345
359
EN
Mohammad
Modarres
Industrial Engineering Department, Sharif University of Technology, Tehran, Iran
Mahsa
Ghandehari
Industrial Engineering Department, Sharif University of Technology, Tehran, Iran
In this paper, we first introduce a generalized version of open shop scheduling (OSS), called generalized cyclic open shop scheduling (GCOSS) and then develop a hybrid method of metaheuristic to solve this problem. Open shop scheduling is concerned with processing n jobs on m machines, where each job has exactly m operations and operation i of each job has to be processed on machine i . However, in our proposed model of GCOSS, processing each operation needs more than one machine (or other resources) simultaneously. Furthermore, the schedule is repeated more than once. It is known that OSS is NP-hard. Therefore, for obtaining a good solution for GCOSS, which is obviously NP-hard, a hybrid algorithm is also developed. This method is constructed by hybridizing ant colony optimization (ACO), beam search and linear programming (LP). To verify the accuracy of the method, we also compare the results of this algorithm with the optimal solution for some special problems.
Open shop scheduling,Cyclic open shop scheduling,Metaheuristic,ACO, Beam
search
http://www.jise.ir/article_3946.html
http://www.jise.ir/article_3946_8947ade6522a354f9ea241f3ff7e4d33.pdf
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
1
4
2008
01
01
Study of Scheduling Problems with Machine Availability Constraint
360
383
EN
Hamid Reza
Dehnar Saidy
Young Researchers Club, Tehran’s Science and Research Branch, Islamic Azad University, Tehran, Iran
Mohammad
Taghi Taghavi-Fard
Faculty of Accounting and Management, Allameh Tabataba’i University, Tehran, Iran
In real world scheduling applications, machines might not be available during certain time periods due to deterministic or stochastic causes. In this article, the machine scheduling with availability constraints for both deterministic and stochastic cases with different environments, constraints and performance measures will be discussed. The existing body of research work in the literature will be completely reviewed and the NP-complete models will be identified.
sequencing,scheduling,Unavailability period,Resumable,Breakdown,NP-hard
http://www.jise.ir/article_3947.html
http://www.jise.ir/article_3947_3079cef8543b240e3911a82b271fbf27.pdf