Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
24
3
2017
06
01
Vendor-managed inventory system with partial backordering for evaporating chemical raw material
1483
1492
EN
A.A.
Taleizadeh
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran.
10.24200/sci.2017.4129
Consider a supply chain including a renery producing evaporating chemical product, an exporter, and one or some engine oil producers outside the exporter's country. The exporter uses vendor-managed inventory system implemented between renery and exporter to decrease his/her inventory cost. This paper develops two models with partial backordering for evaporating chemical product developed in a two-layer chain includingsingle renery and single exporter with one product before and after utilizing vendormanaged inventory policy. Demand and partial backordering rates are deterministic and constant. A numerical example is provided to illustrate the applicability of the proposed model and solution method.
Supply chain management,Inventory,Partial backordering,Evaporating product,Deterioration
http://scientiairanica.sharif.edu/article_4129.html
http://scientiairanica.sharif.edu/article_4129_8b0ae9b4308b2991e6dcf996d8a4884e.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
24
3
2017
06
01
Sequencing of mixed models on U-shaped assembly lines by considering effective help policies in make-to-order environment
1493
1504
EN
M.
Rabbani
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, P.O. Box 11155-4563, Iran
N.
Manavizadeh
Department of Industrial Engineering, Khatam University, Tehran, Iran.
N.
Shabanpour
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, P.O. Box 11155-4563, Iran
10.24200/sci.2017.4130
Mixed-Model Assembly Line (MMAL) is a type of production line where a variety of products' models similar to products' characteristics are assembled in the same line. Many manufacturers tend to use mixed-model assembly line in their production lines, since this policy makes it possible to assemble various products in the Make-To-Order (MTO) environment. In this research, the sequence of U-type mixed-model assembly lineis achieved through considering downstream help and storage of kits as eective help policies for reducing total line stoppages and tardiness in delivery time of products to customers. Since this problem is NP-hard, hybrid GA-Beam search algorithm is developed to solve the problem. Numerical experiments are used to evaluate the performance and effectiveness of the proposed algorithm. To the best of our knowledge, this is the first study that considers getting help from downstream worker or using storehouse of kits, which has ready-toassemble parts in the conditions that workers cannot complete the remained task in the work horizon.
MMAL,MTO,Kits' storage,Downstream help,Hybrid GA-beam search
http://scientiairanica.sharif.edu/article_4130.html
http://scientiairanica.sharif.edu/article_4130_15ad642dd9480e7631ebdeccacc68678.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
24
3
2017
06
01
A projection-based approach to intuitionistic fuzzy group decision making
1505
1518
EN
Z.
Yue
College of Mathematics and Computer Science, Guangdong Ocean University, Zhanjiang, China
Y.
Jia
Library of Guangdong Ocean University, Zhanjiang, China
10.24200/sci.2017.4131
Group Decision Making (GDM) is usually used for solving complex decision problems, which is an important part of modern decision science. Weight of the Decision Maker (DM) plays an important role in the GDM process, and the projection-based approach is a comprehensive consideration between decision objects. It is a valuable work to determine the weights of DMs by a projection measurement. This paper investigates a GDMmethod based on projection measurement in an intuitionistic fuzzy environment. First, this article introduces an ideal decision among all individual decisions, and the weights of DMs are determined by using a projection measurement. Then, the individual decisions are aggregated into a collective decision. Finally, the preference order of alternatives is identied by using the score and accuracy function of the intuitionistic fuzzy numbers.In addition, a comparison with another GDM method is provided. Feasibility and practicability of the developed method are illustrated by an experimental analysis. The experimental result shows that the projection-based method is a high-resolution decision method.
group decision making,Intuitionistic fuzzy number,Weight of decision maker,Projection measurement,Aggregation
http://scientiairanica.sharif.edu/article_4131.html
http://scientiairanica.sharif.edu/article_4131_b13c47748cd8c9b24dd7f0c11129e446.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
24
3
2017
06
01
Development of a Cournot-oligopoly model for competition of multi-product supply chains under government supervision
1519
1532
EN
A.
Hafezalkotob
College of Industrial Engineering, Islamic Azad University, South Tehran Branch, Entezari Alley, Oskoui Alley, Choobi Bridge,
Tehran, P.O. Box 1151863411, Iran
S.
Borhani
College of Industrial Engineering, Islamic Azad University, South Tehran Branch, Entezari Alley, Oskoui Alley, Choobi Bridge,
Tehran, P.O. Box 1151863411, Iran
S.
Zamani
College of Industrial Engineering, Islamic Azad University, South Tehran Branch, Entezari Alley, Oskoui Alley, Choobi Bridge,
Tehran, P.O. Box 1151863411, Iran
10.24200/sci.2017.4132
Globalization, increased governmental regulations, and customer demands regarding environmental issues have led the organizations to review the measures necessary for the implementation of the Green Supply Chain Management (GSCM) to improve the environmental and economical performances. The paper proposes a Cournot-oligopoly model for green supply chain management. It provides a novel approach to construct amodel that maximizes government tari and prots of the suppliers and manufacturers in all the GSCs. The bi-level model is converted to a single-level model by replacing the second level with its Karush Kuhn Tucker (KKT) conditions and linearization techniques. Then, a Genetic Algorithm (GA) is utilized to solve the single-level model using MATLAB software. Afterwards, the obtained results are compared with optimal solutions acquired by Enumerative Method (EM) to evaluate the validity and feasibility of the proposed GA. The sensitivity analysis of this model indicates that the scal policy of the government greatly affects the reduction of environmental pollution costs caused by industrial activities such as automobile production in a competitive market. Therefore, the amount of non-green products' taxes is directly related to the decrease of environmental pollution.
http://scientiairanica.sharif.edu/article_4132.html
http://scientiairanica.sharif.edu/article_4132_ebf263e545f6210e8576949c41abe4f8.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
24
3
2017
06
01
A robust optimization approach for an inventory problem with emergency ordering and product substitution in an uncertain environment: A case study in pharmaceutical industry
1533
1546
EN
E.
Mardan
Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
M.
Sadegh Amalnick
Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
M.
Rabbani
Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
F.
Jolai
Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
gmzvcalo@scientiaunknown.non
10.24200/sci.2017.4133
This paper presents a multi-product, multi-period inventory problem in an uncertain environment where the main suppliers are prone to yield uncertainty. In order to overcome the arisen uncertainties, two basic approaches of emergency ordering and product substitutability are taken into consideration. In the proposed emergency ordering scheme, two sets of suppliers, i.e. cheap unreliable and expensive reliable (emergency) suppliers, are considered and a tradeo between the cheap price of the main suppliers and reliabilityof emergency supplier is attained. In product substitution scheme, the demand of each product is fullled directly by the related product or other substitute products. A riskaverse decision maker is taken into consideration whose risk-averseness level is controlled by the portion of demand which should be denitely satised and not backordered or lost. A robust optimization approach with two variability measures is proposed to minimize the variability of the model. The results reveal the value of emergency ordering and productsubstitution. In addition, the results suggest which measure should be selected according to the decision maker's attitude toward the desired prot, variability, and service level.
Substitutable products,Emergency ordering,Yield uncertainty,Inventory problem
http://scientiairanica.sharif.edu/article_4133.html
http://scientiairanica.sharif.edu/article_4133_f41d626a0c12eda244631ea7827a2885.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
24
3
2017
06
01
Solving the redundancy allocation problem of k-out-of-n with non-exponential repairable components using optimization via simulation approach
1547
1560
EN
P.
Azimi
Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
p.azimi@yahoo.com
M.
Hemmati
Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
m_hemmati@aut.ac.ir
A.
Chambari
Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
10.24200/sci.2017.4134
In this article, a new model and a novel solving method are provided to address the non-exponential redundancy allocation problem in series-parallel k-out-of-n systems with repairable components based on Optimization Via Simulation (OVS) technique. Despite the previous studies, in this model, the failure and repair times of each component were considered to have non-negative exponential distributions. This assumption makes the model closer to the reality where the majority of used components have greater chance to face a breakdown in comparison to new ones. The main objective of this research is the optimization of Mean Time to the First Failure (MTTFF) of the system via allocating the best redundant components to each subsystem. Since this objective function of the problem could not be explicitly mentioned, the simulation technique was applied to model the problem, and dierent experimental designs were produced using DOE methods. To solve the problem, some meta-Heuristic Algorithms were integrated with the simulation method. Several experiments were carried out to test the proposed approach; as a result, the proposed approach is much more real than previous models, and the near optimum solutions are also promising.
Redundancy Allocation Problem,k-out-of-n systems,meta-heuristic algorithms,Simulation Methods,Enterprise Dynamic (ED) software
http://scientiairanica.sharif.edu/article_4134.html
http://scientiairanica.sharif.edu/article_4134_eab1f7aed4b74bb17b82ae2a57e7325f.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
24
3
2017
06
01
Fuzzy multi-objective optimization of linear functions subject to max-arithmetic mean relational inequality constraints
1561
1570
EN
F.
Kouchakinejad
Department of Mathematics, Graduate University of Advanced Technology, End of Haft Bagh-e-Alavi Highway, Kerman, Iran
M.
Mashinchi
Department of Statistics, Faculty of Mathematics and Computer Science, Shahid Bahonar University of Kerman, Pajohesh Square, 22nd Bahman Blvd, Kerman, Iran
fvjdicgp@scientiaunknown.non
E.
Khorram
Faculty of Mathematics and Computer Sciences, Amirkabir University of Technology, 424 Hafez Ave, Tehran, Iran.
10.24200/sci.2017.4135
The main goal of this work is to nd a better solution to a kind of multiobjective optimization problem subject to a system of fuzzy relational inequalities with max-arithmetic mean composition. First, this problem is solved and, then, in the case that the decision maker is not satised with any of the solutions, by assigning linear membership functions to the inequalities in the constraints and objective functions and using Bellman-Zadeh decision, a new solution is found. This new solution does not belong to the feasible domain but is considered acceptable based on the decision maker's view. In order to found this solution easier, some simplication processes are given. Afterwards, an algorithm is presented to generate the new solution. Finally, an example is given to illustrate the steps of the algorithm.
Fuzzy inequality,Fuzzy relational inequalities,Fuzzy solution,Linear objective function,Max-arithmetic mean composition,Multi-objective optimization
http://scientiairanica.sharif.edu/article_4135.html
http://scientiairanica.sharif.edu/article_4135_0a276849c3dae68b89c77b153ab921c4.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
24
3
2017
06
01
A new proactive-reactive approach to hedge against uncertain processing times and unexpected machine failures in the two-machine flow shop scheduling problems
1571
1584
EN
D.
Rahmani
Department of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran
10.24200/sci.2017.4136
In this paper, a proactive-reactive approach has been considered for achieving stable and robust schedules despite uncertain processing times and unexpected machine failures in a two-machine flow shop system. In the literature, Surrogate Measures (SMs) have been developed for achieving stable and robust solutions against the occurrence of stochastic disruptions. These measures proactively provide an approximation of the real conditions of the system in the event of a disruption. Because of the discrepancies of these measures with their real values, a dierent approach is developed in this paper in two-step structure. First, an initial robust schedule is produced and then, based on a multi-component measure, an appropriate reaction is adopted against unexpected machine failures. Computational results indicate that this method produces better solutions compared to the other two classical scheduling approaches considering their eectivenessand performance.
Disruption,robustness,stability,Nervousness,Flow shop,Proactive-reactive approach
http://scientiairanica.sharif.edu/article_4136.html
http://scientiairanica.sharif.edu/article_4136_458f9edb40148e46e3b1b1bf7d7b51f2.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
24
3
2017
06
01
A bi-objective model to optimize reliability and cost of k-out-of-n series-parallel systems with tri-state components
1585
1602
EN
Pe.
Pourkarim Guilani
Young Researchers and Elite Club, Qazvin Branch, Islamic Azad University, Qazvin, Iran
A.
Zaretalab
Department of Industrial Engineering, Amirkabir University of Technology, 424 Hafez Ave., Tehran, Iran
S.T.
A. Niaki
Department of Industrial Engineering, Sharif University of Technology, Tehran, P.O. Box 11155-9414, Iran
Pa.
Pourkarim Guilani
Young Researchers and Elite Club, Qazvin Branch, Islamic Azad University, Qazvin, Iran.
10.24200/sci.2017.4137
Redundancy Allocation Problem (RAP) is one way to increase system reliability. In most of the models developed so far for the RAP, system components are considered to have a binary state consisting of working perfect" or completely failed". However, to suit the real-world applications, this assumption has been relaxedin this paper, such that components can have three states. Moreover, a Bi-Objective RAP (BORAP) is modeled for a system with serial subsystems, in which non-repairable tri-state components of each subsystem are congured in parallel and the subsystem works under k-out-of-n policy. Furthermore, to enhance system reliability, technical and organizational activities that can aect failure rates of the components, and hence can improve the system performance are also taken into account. The aim is to nd the optimum number of redundant components in each subsystem, such that the system reliability is maximized while the cost is minimized within some real-world constraints. In order to solve the complicated NP-hard problem at hand, the multi-objective Strength Pareto EvolutionaryAlgorithm (SPEA-II) is employed. As there is no benchmark available, the Non-dominated Sorting Genetic Algorithm (NSGA-II) is used to validate the results obtained. Finally, theperformances of the algorithms are analyzed using 20 test problems.
Reliability,Redundancy Allocation Problem,Tri-state components,Bi-objective optimization,SPEA-II
http://scientiairanica.sharif.edu/article_4137.html
http://scientiairanica.sharif.edu/article_4137_fe5f2d01eddabc7d801fe5e36f01148e.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
24
3
2017
06
01
Monitoring of serially correlated processes using residual control charts
1603
1614
EN
R.
Osei-Aning
Department of Mathematics and Statistics, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia
S.A.
Abbasi
Department of Mathematics and Statistics, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia
M.
Riaz
Department of Mathematics and Statistics, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia
10.24200/sci.2017.4138
Control charts act as the most important tool for monitoring of process parameters. The assumption of independence that underpins the implementation of the charts is violated when process observations are correlated. The eect of this issue can lead to the malfunctioning of the usual control charts by causing a large number of false alarms or slowing the detection ability of the chart in unstable situations. In this paper, weinvestigated the performance of the Mixed EWMA-CUSUM and Mixed CUSUM-EWMA charts for the ecient monitoring of autocorrelated data. The charts are applied to the residuals obtained from tting an autoregressive (AR) model to the autocorrelated observations. The performance of these charts is compared with the performances of the residual Shewhart, EWMA, CUSUM, combined Shewhart-CUSUM, and combinedShewhart-EWMA charts. Performance criteria such as Average Run Length (ARL) and Extra Quadratic Loss (EQL) are used for the evaluation and comparison of the charts. Illustrative examples are presented to demonstrate the application of the charts to serially correlated observations
Autocorrelation,Average Run Length,CUSUM,EWMA,Extra Quadratic Loss,Residuals
http://scientiairanica.sharif.edu/article_4138.html
http://scientiairanica.sharif.edu/article_4138_561a0fe1bf01766e340e58342fcc4fdc.pdf