2018
25
4
4
141
http://scientiairanica.sharif.edu/4451.html
10.24200/sci.2017.4451
Biobjective scheduling for the reentrant hybrid flow shop with learning effect and setup times
2
2
The production scheduling problem in hybrid flow shops is a complex combinatorial optimization problem observed in many realworld applications. The standard hybrid flow shop problem involves often unrealistic assumptions. In order to address the realistic assumptions, four additional traits were added to the proposed problem. These include reentrant line, setup times, positiondependent learning effects, and the consideration of maximum completion time together with total tardiness as objective function. Since the proposed problem is nondeterministic polynomialtime (NP)hard, a metaheuristic algorithm is proposed as the solution procedure. The solution procedure is categorized as an a priori approach. To show the efficiency and effectiveness of the proposed algorithm, computational experiments were done on various test problems. Computational results show that the proposed algorithm can obtain an effective and appropriate solution quality for our investigated problem
2

2233
2253


S.M.
Mousavi
Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran
Iran
mousavi.sme@gmail.com


I.
Mahdavi
Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran
Iran


J.
Rezaeian
Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran
Iran


M.
Zandieh
Department of Industrial Management, Management and Accounting Faculty, Shahid Beheshti University, G. C., Tehran, Iran
Iran
Reentrant hybrid flow shop
Setup times
learning effect
Multiobjective problems
A priori approach
http://scientiairanica.sharif.edu/4535.html
10.24200/sci.2017.4535
Pricing and advertising decisions in a dominantretailer supply chain: A multifollower bilevel programming approach
2
2
Pricing and advertising is one of the most important decisions in each supply chain especially in the competitive environment. In the previous studies, this is as a centralized decision. However, if each channel member makes its decision independently, the utility of all members is optimized. In such decentralized situations, the channel members may have different market power that they influence on the other members’ decisions. These issues can modeled through leaderfollower Stackelberg game or bilevel programming. This study investigates coordination of pricing and cooperative advertising in a twostage supply chain consisting of one dominantretailer and multiple competitive manufactures which produce several perishable and substitutable products. This paper aims to determine pricing and cooperative advertising decisions expenditure as well as the amount of manufacturers’ production or retailer’s purchase such that utility of all members is met. Hence, the problem is modeled as a multifollower bilevel programming problem. Since it is proved that the model is NPhard, the proposed model is solved through simulated annealing. A numerical example is used to show the impact of demand’s variations on the members’ decisions.
2

2254
2266


Maryam
Mokhlesian
Faculty of Industrial & Systems Engineering, Tarbiat Modares University, Tehran, Iran
Iran


Seyed Hessameddin
Zegordi
Faculty of Industrial & Systems Engineering, Tarbiat Modares University, Tehran, Iran
Iran
Bilevel Programming
Pricing
Dominantretailer supply chain
Substitutable and perishable products
cooperative advertising
Simulated annealing
http://scientiairanica.sharif.edu/4458.html
10.24200/sci.2017.4458
Optimization of multiresponse problems with continuous functional responses by considering dispersion effects
2
2
In some processes, quality of a product should be characterized by functional relationships between response variables and a signal factor. Hence the traditional methods cannot be used to find the optimum solution. In this paper, we propose a method which considers two different dispersion effects, i.e. in domain and between replicates variations in the functional responses. Besides, we propose an integral based measure to find the deviation from target function. A probabilistic method is applied to consider the correlation structure of functional responses. Three numerical examples and a real case from literature are studied to show the efficiency of the proposed method
2

2267
2281


Mohammad Hasan
Bakhtiarifar
Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran
Iran


Mahdi
Bashiri
Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran
Iran
bashiri@shahed.ac.ir


Amirhossein
Amiri
Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran
Iran
amirhossein.amiri@gmail.com
Multiple Responses Optimization
Functional Responses
Design of Experiments
Polynomial integral
http://scientiairanica.sharif.edu/4452.html
10.24200/sci.2017.4452
Optimizing the number of outbound doors in the crossdock based on a new queuing system with the assumption of beta arrival time
2
2
Crossdocking is one of the supply chain strategies that can reduce transportation and inventory costs. Many studies are conducted the problem of crossdocking by considering various characteristics of crossdocks. In this paper, a queuing model is proposed in order to optimize the number of outbound doors based on minimizing the total costs including the costs of adding a new outbound door and the expected waiting time of customers. The total number of trucks arriving for service is constant. Trucks arrive to outbound doors of the crossdock within a specified time window. Arrival times of trucks follow a beta distribution and customers to be served based on first in first out policy (FIFO). Since, the total number of customers as well as the time of arrivals are finite, the steady state distribution for the long run of the system is inapplicable. Instead, based on conditional joint probabilities, order statistics along with the Bayes theorem we calculate the total expected waiting time.
2

2282
2296


A.
MotaghediLarijani
Amirkabir University of Technology, Tehran, Iran
Iran


M.
Aminnayeri
Amirkabir University of Technology, Tehran, Iran
Iran
wxyjzzje@scientiaunknown.non
crossdock
queuing system
nonstationary
order statistics
conditional probability
http://scientiairanica.sharif.edu/4456.html
10.24200/sci.2017.4456
Robustfuzzy model for supplier selection under uncertainty: An application to the automobile industry
2
2
This paper proposes an innovative robustfuzzy method for multiobjective, multiperiod supplier selection problem under multiple uncertainties. This approach integrates robust optimization and fuzzy programming. Uncertain parameters are modeled as random variables that take value within a symmetrical interval. However, due to the complexity or ambiguity of some real world problems and specially the nature of some of the available input data, the length of interval is also highly uncertain. This ambiguity motivated us to present a new approach, which can be applicable to multiple uncertainties conditions. Thus, in our approach the halflength of these intervals is also represented by fuzzy membership function. We develop a model and a solution approach to select suppliers by considering risk. The proposed method is applied to a real case of supplier selection in automobile industry under uncertainty and ambiguity conditions. To verify the proposed model, we evaluated the results by simulation technique and compared values of objective function under different scenarios.
2

2297
2311


Masood
Rabieh
Department of Industrial Management, Shahid Beheshti University, Tehran, Iran
Iran


Mohammad
Modarres
Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran
Iran
modarres@sharif.edu


Adel
Azar
Department of Industrial Management, Tarbiat Modares University, Tehran, Iran
Iran
azara@modares.ac.ir
Supplier selection
uncertainty
robust optimization
Fuzzy programming
Robustfuzzy model
Auto industry
http://scientiairanica.sharif.edu/4450.html
10.24200/sci.2017.4450
A clusterbased emergency vehicle routing problem in disaster with reliability
2
2
In the event of natural disasters, relief distribution is the most challenging problem of emergency transportation. What is important in response to disaster is victims’ relief in disaster areas with the quick distribution of vital commodity. In this regard, damage to infrastructure (e.g., roads) can make trouble in designing a distribution network. So, this paper considers a problem using a threestage approach. In the first stage, preprocessing of model inputs is done through an artificial neural fuzzy inference system (ANFIS) followed by investigating the safest route for each cluster using of decisionmaking techniques and graph theory. In the second stage, a heterogeneous multidepots multimode vehicle routing problem is formulated for minimizing the transportation time and maximize the reliability. Finally, since the routing problem is NPhard, two multiobjective metaheuristic algorithms, namely nondominated sorting genetic algorithm (NSGAII) and multiobjective firefly algorithm (MOFA), are proposed to obtain the optimal solution and compared their performance through a set of randomly generated test problems. The results show that for this routing problem, the MOFF gives better solutions in comparison to NSGAII and performs well in terms of accuracy and solution time.
2

2312
2330


Zahra
Gharib
Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Iran


Ali
BozorgiAmiri
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
Iran


Reza
TavakkoliMoghaddam
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
Iran
tavakoli@gmail.com


Esmaeil
Najafi
Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Iran
disaster
Relief distribution
Vehicle routing problem
Clustering
Reliability
multiobjective metaheuristics
http://scientiairanica.sharif.edu/4453.html
10.24200/sci.2017.4453
Multimachine economic production quantity for items with scrapped and rework with shortages and allocation decisions
2
2
This study considers a multiproduct multimachine economic production quantity inventory problem in an imperfect production system that produces two types of defective items: items that require rework and scrapped items. The shortage is allowed and fully backordered. The scrapped items are disposed with a disposal cost and the rework is done at the end of the normal production period. Moreover, a potential set of available machines for utilization is considered such that each has a specific production rate per item. Each machine has its own utilization cost, setup time and production rate per item. The considered constraints are initial capital to utilize machines and production floor space. The proposed inventory model is a mixed integer nonlinear programing mathematical model. The problem is solved using a bilevel approach, first, the set of machines to be utilized and the production allocation of items on each machine are obtained thru a genetic algorithm. Then, using the convexity attribute of the second level problem the optimum cycle length per machine is determined. The proposed hybrid genetic algorithm outperformed conventional genetic algorithm and a GAMS solver, considering solution quality and solving time. Finally, a sensitivity analysis is also given.
2

2331
2346


Amir Hossein
Nobil
Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Iran
amirhossein.nobil@yahoo.com


Amir Hosein
Afshar Sedigh
Department of Information Science, University of Otago, Dunedin, New Zealand
New Zealand


Leopoldo Eduardo
CárdenasBarrón
School of Engineering and Sciences
Tecnológico de Monterrey
Ave. E. Garza Sada 2501 Sur, C.P. 64849, Monterrey, Nuevo León, México
Mexico
EPQ
defective item
MINLP
Shortage
Hybrid algorithm
http://scientiairanica.sharif.edu/4457.html
10.24200/sci.2017.4457
Inventory of complementary products with stockdependent demand under vendormanaged inventory with consignment policy
2
2
This paper proposes an integrated twostage model, which consists of one vendor and one buyer for two complementary products. The vendor produces two types of products and delivers them to the buyer in distinct batches. Buyer stocks items in the warehouse and on the shelf. The demand for each product is sensitive to stock levels of both products. A vendor managed inventory with consignment stock policy is considered. The number of shipments and replenishment lot sizes are jointly determined as decision variables in such a way that total profit is maximized. The numerical study shows that as complementary rate increases, the quantity of transfers and demand of both products increase. Hence, ignoring the complementation between products leads to some customers lost.
2

2347
2360


M.
Hemmati
Department of Industrial Engineering, Amirkabir University of Technology, 424 Hafez avenue, 1591634311, Tehran, Iran
Iran
m_hemmati@aut.ac.ir


S.M.T.
Fatemi Ghomi
Department of Industrial Engineering, Amirkabir University of Technology, 424 Hafez avenue, 1591634311, Tehran, Iran
Iran
fatemi@aut.ac.ir


Mohsen S.
Sajadieh
Department of Industrial Engineering, Amirkabir University of Technology, 424 Hafez avenue, 1591634311, Tehran, Iran
Iran
supply chain coordination
Inventory control
Complementary products
Stock dependent demand
Consignment
vendor managed inventory
http://scientiairanica.sharif.edu/4455.html
10.24200/sci.2017.4455
Efficient ratiotype estimators of finite population mean based on correlation coefficient
2
2
We proposed efficient families of ratiotype estimators to estimate finite population mean using known correlation coefficient between study variable and auxiliary variable by adopting Singh and Tailor [Singh, H. P., and Tailor, R. “Use of known correlation coefficient in estimating the finite population means”, Statistics in Transition, 6(4), pp. 555560 (2003)] estimator and Kadilar and Cingi [Kadilar, C., and Cingi, H. “An improvement in estimating the population mean by using the correlation coefficient”, Hacettepe Journal of Mathematics and Statistics, 35(1) pp. 103109. (2006a)] class of estimators in simple random sampling without replacement. The newly proposed estimators behave efficiently as compared to the common unbiased estimator, traditional ratio estimator and the other competing estimators. Bias, mean squared error and minimum mean squared error of the proposed ratiotype estimators are derived. Moreover, theoretically findings are proved with cooperation of two real data sets.
2

2361
2372


Muhammad
Irfan
Department of Mathematics, Institute of Statistics, Zhejiang University, Hangzhou 310027, China
China
mirfan@zju.edu.cn


Maria
Javed
Department of Mathematics, Institute of Statistics, Zhejiang University, Hangzhou 310027 China
Iran


Zhengyan
Lin
Department of Mathematics, Institute of Statistics, Zhejiang University, Hangzhou 310027 China.
China
zlin@zju.edu.cn
Auxiliary variable
Bias
Correlation Coefficient
Efficiency
Mean squared error
Ratiotype estimators
http://scientiairanica.sharif.edu/4454.html
10.24200/sci.2017.4454
A novel correlation coefficient of intuitionistic fuzzysets based on the connection number of set pair analysis and its application
2
2
Set pair analysis (SPA) is an updated theory for dealing with the uncertainty, which overlaps the othertheories of uncertainty such as probability, vague, fuzzy and intuitionistic fuzzy set (IFS). Considering thefact that the correlation coecient plays an important role during the decisionmaking process, in this paper,after pointing out the weakness of the existing correlation coecients between the IFSs, we propose a novelcorrelation coecient and weighted correlation coecients formulation to measure the relative strength of thedierent IFSs. For it, rstly corresponding to each intuitionistic fuzzy number, the connection number of theSPA theory has been formulated in the form of the degree of identity, discrepancy and contrary and thenbased on its, a novel correlation coecient measures have been dened. Pairs of identity, discrepancy andcontrary of the connection number have been taken as a vector representation during the formulation. Lastly,a decisionmaking approach based on the proposed measures has been presented which has been illustratedby two numerical examples in pattern recognition and medical diagnosis.
2

2373
2388


Harish
Garg
School of Mathematics, Thapar University Patiala 147004, Punjab, India
India
harishg58iitr@gmail.com


Kamal
Kumar
School of Mathematics, Thapar University Patiala 147004, Punjab, India
India
Set pair analysis
Connection number
Intuitionistic fuzzy set
Pattern recognition
Medical diagnosis
decision making