2012
5
10
10
72
1

Analysing Price, Quality and Lead Time Decisions with the Hybrid Solution Method of Fuzzy Logic and Genetic Algorithm
http://www.qjie.ir/article_111.html
1
In this paper, the problem of determining the quality level, lead time for order delivery and price of a product produced by a manufacturer is considered. In this problem the demand for the product is influenced by all three decision variables: price, lead time and quality level. To formulate the demand function, a fuzzy rule base that estimates the demand value based on the three decision variables is developed. To doso, the linguistic knowledge of experts in the form of ifthen rules is used to establish the fuzzy system. Moreover, in order to solve the problem, a genetic algorithm integrating the fuzzy rule base is proposed. Finally, to support the validity of the proposed solution, a numerical study is provided.
0

1
9


amin
mahmoudi
Department of Industrial and mechanical Engineering, Islamic Azad University, Qazvin branch, Qazvin, Iran
Iran
amin.mahmoudi10@yahoo.com


hassan
shavandi
Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran
Iran
shavandi@sharif.edu


khashayar
nouhi
Department of Industrial and mechanical Engineering, Islamic Azad University, Qazvin branch, Qazvin,
Iran
Khashayar_nouhi@yahoo.com
Fuzzy Logic
Linguistic variable
Genetic Algorithm
Pricing
Quality level
Lead time
1

A Neural Network Model Based on Support Vector Machine for Conceptual Cost Estimation in Construction Projects
http://www.qjie.ir/article_120.html
1
Estimation of the conceptual costs in construction projects can be regarded as an important issue in feasibility studies. This estimation has a major impact on the success of construction projects. Indeed, this estimation supports the required information that can be employed in cost management and budgeting of these projects. The purpose of this paper is to introduce an intelligent model to improve the conceptual costaccuracy during the early phases of the life cycle of projects in construction industry. A computationally efficient model, namely support vector machine model, is developed to estimate the conceptual costs of construction projects. The proposed neural network model is trained by a cross validation technique in order to produce the reliable estimations. To demonstrate the performance of the proposed model, twopowerful intelligent techniques, namely nonlinear regression and backpropagation neural networks (BPNNs), are provided. Their results are compared on the basis of the available dataset from the related literature in construction industry. The computational results illustrate that the presented intelligent model performs better than the other two powerful techniques.
0

11
18


Behnam
Vahdani
Instructor, Industrial engineering research center, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Iran
b.vahdani@gmail.com


Seyed Meysam
Mousavi
Ph.D. Student, Young Researches Club, South Tehran Branch , Islamic Azad University, Tehran, Iran
Iran


Morteza
Mousakhani
Associate Professor, Department Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran
Iran


Mani
Sharifi
Assistant Professor, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Iran
qjmd@qiau.ac.ir


Hassan
Hashemi
M.Sc, Young Researches Club, South Tehran Branch, Islamic Azad University, Tehran, Iran
Iran
Construction Projects
Conceptual cost estimation
Support vector machine
Cross validation
1

An Integrated Model of Project Scheduling and Material Ordering: A Hybrid Simulated Annealing and Genetic Algorithm
http://www.qjie.ir/article_96.html
1
This study aims to deal with a more realistic combined problem of project scheduling and material ordering. The goal is to minimize the total material holding and ordering costs by determining the starting time of activities along with material ordering schedules subject to some constraints. The problem is first mathematically modelled. Then a hybrid simulated annealing and genetic algorithm is proposed tosolve it. In addition, some experiments are designed and the Taguchi method is employed to both tune the parameters of the proposed algorithm and to evaluate its performance. The results of the performance analysis show the efficiency of the proposed methodology.
0

19
27


Nima
Zoraghi
Islamic Azad University, Qazvin Branch
Iran
Nima.zoraghi@gmail.com


Amir Abbas
Najafi
K.N. Toosi University of Technology
Iran
aanajafi@kntu.ac.ir
سید تقی
اخوان نیاکی
Seyed Taghi
Akhavan Niaki
Sharif University of Technology
Iran
niaki@sharif.edu
Project Scheduling
Material ordering
Hybrid simulated annealing
Taguchi design
1

Sensitivity Analysis in the QUALIFLEX and VIKOR Methods
http://www.qjie.ir/article_79.html
1
The sensitivity analysis for multiattribute decision making (MADM) problems is important for two reasons: First, the decision matrix as the source of the results of a decision problem is inaccurate because it sorts the alternatives in each criterion inaccurately. Second, the decision maker may change his opinions in a time period because of changes in the importance of the criteria and in the policy of the organization over time. This in turn makes problem solving really timeconsuming. Therefore, the best solution is to do sensitivity analysis.In this regard, this paper considers a sensitivity analysis in the QUALIFLEX method which is a compromise ranking method used for multicriteria decision making (MCDM).
0

29
34


Alireza
Alinezhad
Department of industrial engineering, Islamic Azad University of Qazvin, Iran
Iran
alinezhad_ir@yahoo.com


Nima
Esfandiari
Department of industrial engineering, Islamic Azad University of Qazvin, Iran
Iran
Sensitivity analysis
QUALIFLEX
VIKOR
Multicriteria decision making
Multiattribute Decision Making
1

Design of a Mathematical Model for Logistic Network in a MultiStage MultiProduct Supply Chain Network and Developing a Metaheuristic Algorithm
http://www.qjie.ir/article_121.html
1
Logistic network design is one of the most important strategic decisions in supply chain management that has recently attracted the attention of many researchers. Transportation network design is then one of the most important fields of logistic network. This study is concerned with designing a multistage and multiproduct logistic network. At first, a mixed integer nonlinear programming model (MINLP) is formulated that minimizes transportation and holding costs. Then, a hybrid prioritybased Genetic Algorithm (pbGA) andsimulated annealing algorithm (SA) is developed in two phases to find the optimal solution. The solution is represented by a matrix and a vector. Response Surface Methodology (RSM) is also used to adjust the significant parameters of the algorithm. Finally, several test problems are generated which show that the proposed metaheuristic algorithm can find good solutions in reasonable time spans.
0

35
43


Esmaeil
Mehdizadeh
Assistant Professor, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Iran
emqiau@yahoo.com


Fariborz
Afrabandpei
MSc, Ilam Gas Treating Company, National Iranian Gas Company, Ilam, Iran
Iran
Transportation network
Supply chain management
Metaheuristic Algorithms
Prioritybased Genetic Algorithm
1

A Simulated Annealing Algorithm within the Variable Neighbourhood Search Framework to Solve the Capacitated Facility LocationAllocation
Problem
http://www.qjie.ir/article_125.html
1
In this study, we discuss the capacitated facility locationallocation problem with uncertain parameters in which the uncertainty is characterized by given finite numbers of scenarios. In this model, the objective function minimizes the total expected costs of transportation and opening facilities subject to the robustness constraint. To tackle the problem efficiently and effectively, an efficient hybrid solution algorithm based on several metaheuristics and an exact algorithm is put forward. This algorithm generates neighborhoodsby combining the main concepts of variable neighborhood search, simulated annealing, and tabu search and finds the local optima by using an algorithm that uses an exact method in its framework. Finally, to test the algorithms’ performance, we apply numerical experiments on both randomly generated and standard test problems. Computational experiments show that our algorithm is more effective and efficient in term of CPU time and solutions quality in comparison with CPLEX solver.
0

45
54


Ragheb
Rahmaniani
MSc, Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
Iran
ragheb.rahmaniani@gmail.com


abdosalam
Ghaderi
Assistant Professor, Department of Industrial Engineering, University of Kurdistan, P.C. 6617715177, Sanandaj, Iran
Iran


Mohammad
Saidi Mehrabad
Professor, Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
Iran
Capacitated Facility LocationallocationProblem
Single allocation
Uncertainty
Hybrid Algorithm
1

An Exact Algorithm for the Mode Identity Project Scheduling Problem
http://www.qjie.ir/article_122.html
1
In this paper we consider the nonpreemptive variant of a multimode resource constrained project scheduling problem (MRCPSP) with mode identity, in which a set of project activities is partitioned into disjoint subsets while all activities forming one subset have to be processed in the same mode. We present a depthfirst branch and bound algorithm for the resource constrained project scheduling problem with mode identity. The proposed algorithm is extended with some bounding rules to reduce the size of branch and bound tree. Finally, some test problems are solved and their computational results are reported.
0

55
63


Behrouz
Afshar Nadjafi
Assistant Professor, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Iran
afsharnb@merhr.sharif.edu


Amir
Rahimi
MSc, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Iran
a.rahimi@qiau.ac.ir


Hamid
Karimi
MSc, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Iran
hamidkzz@yahoo.com
Project Scheduling
Branch and Bound
ModeIdentity
MultiMode
Resource Constrained
1

A Mathematical Model and a Solution Method for Hybrid Flow Shop Scheduling
http://www.qjie.ir/article_115.html
1
This paper studies the hybrid flow shop scheduling where the optimization criterion is the minimization of total tardiness. First, the problem is formulated as a mixed integer linear programming model. Then, to solve large problem sizes, an artificial immune algorithm hybridized with a simple local search in form of simulated annealing is proposed. Two experiments are carried out to evaluate the modeland the algorithm. In the first one, the general performance of the model and the proposed algorithm is experimented. In the next one, the presented algorithm is compared against some other algorithms. The results support high performance of the proposed algorithm.
0

65
72


Esmaeil
Najafi
Department of industrial engineering, Science & Research Branch, Islamic Azad University, Tehran, Iran
Iran
najafi1414@yahoo.com


Bahman
Naderi
Department of Industrial Engineering, Faculty of Engineering, University of Kharazmi, Karaj, Iran
Iran
bahman.naderi@aut.ac.ir


Hassan
Sadeghi
Young Researchers Club, Islamic Azad University , Qazvin Branch, Qazvin, Iran
Iran


Mehdi
Yazdani
Department of industrial engineering, Qazvin branch, Islamic Azad University, Qazvin, Iran
Iran
m_yazdani@qiau.ac.ir
Scheduling
Hybrid flow shop
Mathematical model
Mixed integer linear program
Artificial immune algorithm