Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
2
2020
04
01
An effective league championship algorithm for the stochastic multi-period portfolio optimization problem
829
845
EN
A.
Husseinzadeh Kashan
Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, P.O. Box 14115-111, Iran.
a.kashan@modares.ac.ir
M.
Eyvazi
Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, P.O. Box 14115-111, Iran.
A.
Abbasi-Pooya
Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, P.O. Box 14115-111, Iran.
10.24200/sci.2018.20995
The multi-period portfolio optimization models were introduced to overcome the weaknesses of the single-period models via considering a dynamic optimization system. However, due to the nonlinear nature of the problem and rapid growth of the size complexity with increasing the number of periods and scenarios, this study is devoted to developing a novel league championship algorithm (LCA) to maximize the portfolio’s mean-variance function subject to different constraints. A Vector Auto Regression model is also developed to estimate the return on risky assets in different time periods and to simulate different scenarios of the rate of return accordingly. Besides, we proved a valid upper bound of the objective function based on the idea of using surrogate relaxation of constraints. Our computational results based on sample data collected from S&P 500 and 10-year T. Bond indices indicate that the quality of portfolios, in terms of the mean-variance measure, obtained by LCA is 10 to 20 percent better than those of the commercial software. This sounds promising that our method can be a suitable tool for solving a variety of portfolio optimization problems.
portfolio optimization,single and multi-period models,league championship algorithm
https://scientiairanica.sharif.edu/article_20995.html
https://scientiairanica.sharif.edu/article_20995_3256ff49bcf664a4181389ce9c945eab.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
2
2020
04
01
A solution based on fuzzy max-min approach to the bi-level programming model of energy and exiramp procurement in day-ahead market
846
861
EN
Z.
Kaheh
Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran
R.
B. Kazemzadeh
Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran
rkazem@modares.ac.ir
M.K.
Sheikh-El-Eslami
Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran
10.24200/sci.2018.20915
In this paper, we focus on solving the integrated energy and flexiramp procurement problem in the day-ahead market. The problem of energy and ramp procurement could be perfectly analyzed through Stackelberg concept, because of its hierarchical nature of the decision-making process. Such a circumstance is modeled via a bi-level programming, in which suppliers act as leaders and the ISO appear as the follower. The ISO intends to minimize the energy and spinning reserve procurement cost, and the suppliers aim to maximize their profit. To solve the proposed model, a fuzzy max-min approach is applied to maximize the players’ utilities. The objectives and suppliers’ dynamic offers, determined regarding the market clearing prices, are reformulated through fuzzy utility functions. The proposed approach is an effective and simple alternative to the KKT method, especially for problems with non-convex lower-level.
Integrated Energy and Flexiramp Market,Bi-level Programming,Fuzzy Max-Min,Dynamic Pricing
https://scientiairanica.sharif.edu/article_20915.html
https://scientiairanica.sharif.edu/article_20915_45cbec90f50a02b0188476dc115028c6.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
2
2020
04
01
The stage shop scheduling problem: lower bound and metaheuristic
862
879
EN
M.M.
Nasiri
0000-0001-9813-1233
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
mmnasiri@ut.ac.ir
M.
Hamid
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
m.hamid31400@ut.ac.ir
10.24200/sci.2018.5199.1146
Remarkable efforts are made to develop the job shop scheduling problem up to now. As a novel generalization, the stage shop can be defined as an environment, in which each job is composed of some stages and each stage may include one operation or more. A stage can be defined a subset of operations of a job, such that these operations can be done in any arbitrary relative order while the stages should be processed in a predetermined order. In other words, the operations of a stage cannot be initiated until all operations of the prior stage are completed. In this paper, an innovative lower bound based on solving the preemptive open shop (using a linear programming model in polynomial time) is devised for the makespan in a stage shop problem. In addition, three metaheuristics, including firefly, harmony search and water wave optimization algorithms are applied to the problem. The results of the algorithms are compared with each other, the proposed lower bound, and a commercial solver.
Scheduling,Stage shop,Mixed shop,Water Wave Optimization,Lower bound
https://scientiairanica.sharif.edu/article_21119.html
https://scientiairanica.sharif.edu/article_21119_50205ecc975ce43db0505ca7e11c83e1.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
2
2020
04
01
A novel assessment approach to EFQM driven institutionalization using integrated fuzzy multi-criteria decision-making methods
880
892
EN
O.
Uygun
Department of Industrial Engineering, Faculty of Engineering, Sakarya University, Turkey
ouygun@sakarya.edu.tr
S.
Yalcin
Department of Industrial Engineering, Faculty of Engineering and Architecture, Beykent University, Turkey.
selinyalcin@beykent.edu.tr
A.
Kiraz
0000-0001-7067-1473
Department of Industrial Engineering, Faculty of Engineering, Sakarya University, Turkey.
kiraz@sakarya.edu.tr
E.
Furkan Erkan
0000-0002-5470-8333
Department of Industrial Engineering, Faculty of Engineering, Sakarya University, Turkey.
eneserkan@sakarya.edu.tr
10.24200/sci.2018.5398.1259
It is becoming increasingly difficult for enterprises to survive under competitive conditions. Enterprises with high levels of institutionalization are able to survive and benefit more advantages than their competitors. Excellence models are widespread tools for measuring the degree of institutionalization of enterprises. The importance of institutionalization has been increasingly considered in excellence models. EFQM (European Foundation for Quality Management) is a suitable tool to show how successful organizations are in terms of institutionalization. In this study, EFQM criteria are evaluated with fuzzy multi-criteria decision-making techniques. The fuzzy DEMATEL method is used to determine the interactions amongst main EFQM criteria. According to the relationship diagram obtained from the Fuzzy DEMATEL method, the weights of the sub criteria are calculated according to the expert evaluations using Fuzzy Analytic Network Process (FANP) method. The criterion “Business Results” has been determined to be the most important criteria. The criteria weights are taken as input for the VIKOR method. The institutional scores obtained by the proposed method, and the scores given by the EFQM evaluators to the institutions, are statistically analyzed to demonstrate that the proposed method has produced meaningful results.
Computational Organization Performance,EFQM,Excellence models,Fuzzy DEMATEL,Fuzzy ANP,VIKOR
https://scientiairanica.sharif.edu/article_21058.html
https://scientiairanica.sharif.edu/article_21058_93b3e9ee2b28c7475dc05acecd904290.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
2
2020
04
01
The application of multivariate analysis approaches to designing NSBM model considering undesirable variable and shared resources
893
917
EN
H.
Ghasemi Toudeshki
Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
homa.ghasemi63@gmail.com
E.
Najafi
Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
najafi1515@yahoo.com
F.
Hosseinzadeh Lotfi
Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran.
farhad@hosseinzadeh.ir
F.
Movahedi-Sobhani
Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
fmovahedi@iau.ac.ir
10.24200/sci.2018.5578.1392
Due to the competitiveness of banking industry and increasing bargaining power of customers, evaluation of the banks’ performance is crucial to better serve the classified customers in a universal system .In this paper, with consideration of segmenting the customers into personal and business ones, methods such as confirmatory factor analysis (CFA) and structural equation model (SEM) have been used in selecting appropriate variables of the network data envelopment analysis (NDEA) model based on network slacks-based measure and consideration of the undesirable variables and shared resources. The SEM model has been used to establish a proper connection between the different dimension of the NDEA model and CFA model has been used to identify the importance of each dimension. Also, the proposed model has been used to measure the Operational and decomposed universal efficiency of one of the Iranian bank branches (Day Bank). The results show that the extracted model provides managers with a suitable perspective in adopting appropriate policies to promote their performance in the different sectors, including deposit attraction, financial serving personal and business banking customers, and profit generation, and also in comparing them in the different dimensions of the model.
confirmatory factor analysis,structural equation,network data envelopment analysis,network slacks-based measure,universal banking system
https://scientiairanica.sharif.edu/article_21053.html
https://scientiairanica.sharif.edu/article_21053_09c3f73f1dc76477e980df5afeb9bac9.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
2
2020
04
01
Optimal production inventory decision with learning and fatigue behavioral effects in labor-intensive manufacturing
918
934
EN
K.
Fu
Department of Logistics Management, School of Business Administration, Guangdong University of Finance, Guangzhou,
510521, China.
kaifangfu@sina.com
Zh.
Chen
Department of Management Science, School of Business, Sun Yat-Sen University, Guangzhou, 510275, China.
mnsczx@mail.sysu.edu.cn
Y.
Zhang
Department of Management Science, School of Business, Sun Yat-Sen University, Guangzhou, 510275, China.
zhangyr26@mail2.sysu.edu.cn
H.M.
Wee
Department of Industrial Engineering, Chung Yuan Christian University, No. 200, Chung Pei Road, Chung li District, Taoyuan City, 32023, Taiwan.
weehm@cycu.edu.tw
10.24200/sci.2018.50614.1788
Behavioral economic has received much attention recently. Learning and fatigue are two typical behavioral phenomena in industrial production operation processes. The existence of learning and fatigue result in a dynamic change in productivity. In this paper, a classical economic production quantity model is extended to consider the behavioral economic value of learning and fatigue. Based on a real case study, each production cycle is divided into five phases, i.e, the learning phase, stable phase, fatigue phase, fatigue recovery (rest) phase, and the relearning phase. The new production inventory decision model is incorporated with dynamic productivity and learning-stable-fatigue-recovery effect. Numerical simulation and sensitivity analysis show that appropriate rest alleviates employees fatigue and increases productivity, resulting in a lower average production cost. On the other hand, when the rest time is too high, exceeding a certain value, it leads to the decline of the actual labor productivity, resulting in an increase in the average cost of the system.
Behavioral economics,productivity,human factor,learning effect,fatigue effect,production inventory decision
https://scientiairanica.sharif.edu/article_21014.html
https://scientiairanica.sharif.edu/article_21014_3efd208e1213175653d6cea332cfd34b.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
2
2020
04
01
Multi-period configuration of forward and reverse integrated supply chain networks through transport mode
935
955
EN
A.
Eydi
Faculty of Engineering, University of Kurdistan, Sanandaj, Iran
eydi81@yahoo.com
S.
Fazayeli
Department of Industrial Engineering, University of Kurdistan, Sanandaj, Iran
saeed.fazayeli@gmail.com
H.
Ghafouri
Department of Industrial Engineering, University of Kurdistan, Sanandaj, Iran
ghafouri.indeng@yahoo.com
10.24200/sci.2018.5261.1175
Today’s competitive business environment has resulted in increasing attention to social responsibilities and customer’s attitudes. Buying and returning have become a common practice for different reasons, including incompleteness or immature failure of the product or its failure to meet the customer’s satisfaction. Before the buying and returning cycle can be handled appropriately, companies need a proper logistics network designed following a proper design strategic. In the present research, a forward and reverse logistics network is proposed for product distribution and collection. The contribution of this paper to the literature is the proposal of a multi-period, multi-echelon, integrated forward and reverse supply chain network design problem with transportation mode selection considered. Different kinds of decisions including the determination of optimum number and locations of facilities, facilities opening time and transportation mode selection among different facilities have been considered in this paper. Due to multi-period nature of the problem, the problem is flexible for future periods. A new mixed integer nonlinear programming model was proposed for the introduced problem considering different levels of facility capacities with the maximum profit objective function. As another contribution, a genetic algorithm was developed to cope with problem’s complexity when the problem size goes large.
supply chain network design,forward and reverse logistic,multi-period programming,transportation mode,Genetic Algorithm
https://scientiairanica.sharif.edu/article_21061.html
https://scientiairanica.sharif.edu/article_21061_75fec80565c11502de9bc15995fa9a14.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
2
2020
04
01
Innovation and environmental performance: An empirical study of 31 cities in China
956
969
EN
Y.
Li
School of Business, Sichuan University, Wangjiang Road No. 29, Chengdu, 610064, China, P.R.
lynn177@126.com
Y.H.
Chiu
0000-0002-9702-2892
Department of Economics, Soochow University, 56, Kueiyang St., Sec. 1, Taipei 100, Taiwan, R.O.C.
echiu@scu.edu.tw
L.C.
Lu
Department of Economics, Soochow University, 56, Kueiyang St., Sec. 1, Taipei 100, Taiwan, R.O.C.
ryan@phanteks.com
H.
Liu
School of Business, Sichuan University, Wangjiang Road No. 29, Chengdu, 610064, China, P.R.
noah_liuhx@foxmail.com
10.24200/sci.2018.50934.1927
After its rapid economic growth, China is facing a very serious problem of atmospheric pollution with major long-term atmospheric problems appearing in large cities. Air pollution not only affects people’s normal lives, but also has a greater negative impact on their bodies, causing diseases, impacting productivity, and influencing people’s creativity. Due to past articles, the discussion on the efficiency of innovation and research has not been considered the impact of environmental variables. This study combines energy consumption, economics, environmental variables and innovative research and development capabilities to analyze and explore the relationship between consumption, environment, economy, and innovative R&D capabilities, this is the feature of this article.<br />This study employ the Dynamic Data Envelopment Analysis (DEA) model to calculate energy consumption efficiency, R&D input efficiency, innovation patent output efficiency, carbon dioxide emission efficiency, and AQI efficiency of each city and further compare each city to find their space for improvement.<br />The results of the study show that 10 cities have a total efficiency score of 1, implying the improvement space is already 0, whereas the total efficiency scores of the other 21 cities mean there is still much room for improvement, and there are big differences among the cities.
AQI efficiency,energy efficiency,re-sampling,CO2 efficiency,innovation efficiency,SBM DEA
https://scientiairanica.sharif.edu/article_21191.html
https://scientiairanica.sharif.edu/article_21191_c2b2932f402ddc79ed14d0c1e4795969.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
2
2020
04
01
Presenting a series-parallel redundancy allocation problem with multi-state components using recursive algorithm and meta-heuristic
970
982
EN
M.
Sharifi
0000-0002-7682-7077
Faculty of Industrial & Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
m.sharifi@qiau.ac.ir
M.
Saadvandi
Faculty of Industrial & Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran.
saadvandi.m@qiau.ac.ir
M. R.
Shahriari
Faculty of Management & Accounting, South Tehran Branch, Islamic Azad University, Tehran, Iran.
shahriari_mr@gmail.com
10.24200/sci.2018.51176.2040
Redundancy Allocation Problem (RAP) is one of the most important problems in the field of reliability. This problem aims to increase system reliability, under constraints such as cost, weight, etc. In this paper, we work on a system with series-parallel configuration and multi-state components. To draw the problem nearer to real condition, we merge this problem with discount levels in purchasing components. For calculating sub-systems reliability, we used recursive algorithm. Because RAP belongs to Np. Hard problems, for optimizing the presented model a new Genetic algorithm (GA) was used. The algorithm parameters tuned using Response surface methodology (RSM) and for validation of GA an enumeration method was used.
Reliability optimization,Multi-state components,RAP,Recursive algorithm,GA
https://scientiairanica.sharif.edu/article_21134.html
https://scientiairanica.sharif.edu/article_21134_7c1c9d9c2eb3517a45f6fa0e954fc765.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
2
2020
04
01
Project safety evaluation by a new soft computing approach-based last aggregation hesitant fuzzy complex proportional assessment in construction industry
983
1000
EN
H.
Gitinavard
Young Researchers and Elite Club, South Tehran Branch, Islamic Azad University, Tehran, Iran
S.M.
Mousavi
Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran
mousavi.sme@gmail.com
B.
Vahdani
0000-0001-9850-2698
Department of Industrial Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran.
b.vahdani@gmail.com
A.
Siadat
Laboratoire de Conception, Fabrication Commande, Arts et Métier Paris Tech, Centre de Metz, Metz, France
10.24200/sci.2017.4439
In recent years, the implementation of safety management has been increased in construction projects by institutions, and many companies have recognized environmental and social effects of injuries at project work systems. In this regard, a novel decision model is presented based on a new version of complex proportional assessment method with last aggregation under a hesitant fuzzy environment. The decision makers (DMs) assign their opinions by hesitant linguistic variables that are converted to the hesitant fuzzy elements. Also, the DMs’ judgments are aggregated in last step of decision making to decrease information loss. Since weights of the DMs or professional safety experts and evaluation criteria are not equal in practice, a new version of hesitant fuzzy compromise solution method is proposed to compute these weights. In addition, the criteria weights are determined based on proposed hesitant fuzzy entropy method. A real case study in developing countries about the safety of construction projects is considered to indicate the suitability and applicability of the proposed new hesitant fuzzy decision model with last aggregation approach. In addition, an illustrative example is prepared to show that the proposed approach is suitable and reliable in larger size safety problems
Safety evaluation,Construction Projects,Soft computing,group decision making,complex decision analysis,hesitant fuzzy sets (HFSs)
https://scientiairanica.sharif.edu/article_4439.html
https://scientiairanica.sharif.edu/article_4439_0589ca85981cb89803b845d9b95bd70c.pdf