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Sequential optimality conditions provide adequate theoretical tools to justify stopping criteria for nonlinear programming solvers. Here, nonsmooth approximate gradient projection and complementary approximate Karush-Kuhn-Tucker conditions are presented. These sequential optimality conditions are satisfied by local minimizers of optimization problems independently of the fulfillment of constraint qualifications. It is proved that nonsmooth complementary approximate Karush-Kuhn-Tucker conditions are stronger than nonsmooth approximate gradient projection conditions. Sufficiency for differentiable generalized convex programming is established.

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An availability model is developed to optimize the availability of a series repairable system with multiple k-out-of-n subsystems in this paper. There are two types of decision variables that determine the system designer’s decision to allocate the number of repairmen and to allocate the number of redundant components in each subsystem in the presence of weight, volume and cost constraints. As per the nonlinear structure of the objective in the model, the model is located into the nonlinear programming category. A classical Particle Swarm Optimization (PSO) algorithm is proposed to solve seven various instances of the model. The aim of this study is to illustrate the model and to propose an applicable algorithm for the problem. The efficiency of the proposed PSO is illustrated by comparison with Simulated Annealing (SA) method.

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The traffic assignment problem is one of the most important problems for analyzing and optimizing the transportation network to find optimal flows. This study presented a new formulation based on a generalized Benders' decomposition approach to solve its important part, i.e. user equilibrium problems, in deterministic and stochastic cases. The new approach decomposed the problem into a master problem and a sub problem. The first one was a nonlinear and the latter a linear programming problem. Iteratively, the master problem was solved and its outputs were used to solve the sub-problem in which to form appropriate cuts and add them to the master problem for solving it in the next iteration. Based on the convergence of Benders' decomposition, the iterative process was terminated in a finite number of steps. In this manner, some numerical examples were explained and compared with other methods.

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We consider an approximation scheme using Haar wavelets for solving a class of infinite horizon optimal control problems (OCP's) of nonlinear interconnected large-scale dynamic systems. A computational method based on Haar wavelets in the time-domain is proposed for solving the optimal control problem. Haar wavelets integral operational matrix and direct collocation method are utilized to find the approximated optimal trajectory of the original problem. Numerical results are also given to demonstrate the applicability and the efficiency of the proposed method.

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     This special issue is a collection of refereed articles selected from the 13th International Industrial Engineering Conference (IIEC 2017). The initial selection was made by Dr. Hamed Fazlollahtabar who also wrote the following description. The accepted articles were reviewed going through the usual reviewing process of IJOR.

Nezam Mahdavi-Amiri
Editor-in-Chief


     The 13th International Industrial Engineering Conference (IIEC 2017) hosted by Mazandaran University of Science and Technology, Babol, Iran, was held on 22nd and 23rd of February 2017 at Mizban Complex, Babolsar, Mazandaran, Iran. The total number of papers received was 805, among which 378 papers were accepted in two categories of oral presentations (185 papers) and poster presentations (193 papers). The scientific committee of the conference selected a number of papers to be extended and considered for a special issue of the Iranian Journal of Operations Research (IJOR). For this, 25 selected papers were considered and 17 papers were chosen for the second round of review. Having strict review criteria, 11 papers were then selected and refereed for a final decision. After the review process, 6 papers were finally accepted for the special issue. The contents of the accepted papers follow here. Vehicle routing and scheduling in an environmentally friendly manner attracted researchers to develop both mathematical programming models and heuristics as solution approaches. Green supply network design under uncertainty was considered for a multi-mode production system. Facility planning and hub location problem in competitive conditions and multiple allocations were investigated. Robust optimization philosophy as an uncertainty treatment approach was studied using event-driven and attribute-driven concepts. An interesting application of operations research in forestry was studied developing stochastic dynamic programming with Markov chains.

     My special gratitude goes to Professor Nezam Mahdavi-Amiri, Editor-in-chief, and the editorial board members of IJOR for their cooperation and support during the past 10 months of preparing this special issue.

Hamed Fazlollahtabar
Coordinator for Special Issues IIEC2017
Department of Industrial Engineering
School of Engineering, Damghan University
Damghan, Iran

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The definition of ordered weighted averaging (OWA) operators and their applications in decision making are reviewed. Also, some generalizations of OWA operators are studied and then, the notion of 2-symmetric OWA operators is introduced. These generalizations are illustrated by some examples.

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We present a stochastic optimal control approach to wildlife management. The objective value is
the present value of hunting and meat, reduced by the present value of the costs of plant damages
and traffic accidents caused by the wildlife population. First, general optimal control functions and
value functions are derived. Then, numerically specified optimal control functions and value
functions of relevance to moose management in Sweden are calculated and presented.

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Here, we collect two parts of a research project on the pedestrian flow modeling. Rapid growth in the volume of public transport and the need for its reasonable, efficient planning have made the description and modeling of transport and pedestrian behaviors as important research topics in the past twenty years. First, we present a macroscopic model for the pedestrian flow based on continuum mechanical balances. Second, we present a new microscopic modelling method to describe the interaction among pedestrians in conflicting situations. A local navigation based on a continuous density estimator is adopted for the configuration of pedestrians’ temporary route choices on the tactical level. On the operational level, a balancing mechanism is installed to ensure correct execution of the planned position transitions of the pedestrians. A comparison of the test results of our simulation with a real-world video clip is provided.

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In many problems, it is necessary to take into account monotonic relations. Monotonic (isotonic) Regression (MR) is often involved in solving such problems. The MR solutions are of a step-shaped form with a typical sharp change of values between adjacent steps. This, in some applications, is regarded as a disadvantage. We recently introduced a Smoothed MR (SMR) problem which is obtained from the MR by adding a regularization penalty term. The SMR is aimed at smoothing the aforementioned sharp change. Moreover, its solution has a far less pronounced step-structure, if at all available. The purpose of this paper is to further improve the SMR solution by getting rid of such a structure. This is achieved by introducing a lowed bound on the slope in the SMR. We call it Smoothed Slope-Constrained MR (SSCMR) problem. It is shown here how to reduce it to the SMR which is a convex quadratic optimization problem. The Smoothed Pool Adjacent Violators (SPAV) algorithm developed in our recent publications for solving the SMR problem is adapted here to solving the SSCMR problem. This algorithm belongs to the class of dual active-set algorithms. Although the complexity of the SPAV algorithm is $𝑂(𝑛^2)$, its running time is growing in our computational experiments almost linearly with $𝑛$. We present numerical results which illustrate the predictive performance quality of our approach. They also show that the SSCMR solution is free of the undesirable features of the MR and SMR solutions.

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This is a special issue of the Iranian Journal of Operations Research composed of some of the invited talks presented at the 10th International Iranian Operations Research Society (IORS) Conference held in University of Mazandaran, Babolsar, May 3-5, 2017. The IORS conference is an annual event and is the main forum for presenting new theoretical and applied developments of OR within Iran. In recent years, international participation has been promoted to enhance cooperation among internal and external researchers. There were over 400 participants with 186 accepted talks and 138 poster presentations. The selected papers were reviewed going through the usual reviewing process and 7 papers were finally accepted for publication in the current issue.
In the first paper, Adil Bagirov and Sona Taheri develop an algorithm based on optimization for clustering data using an $𝐿_1$-norm. In doing this, they find the Clarke stationary points of the clustering problem and use the points for an effective clustering of data. Comparative test results are presented.
In the second paper, Günter Karl Franz Bärwolff, Minjie Chen and Hartmut Schwandt, concerned with an efficient planning of public transportation systems, propose a simulation of pedestrian flow behaviors by presenting both macroscopic and microscopic models of the pedestrian dynamics. The authors provide comparative test results of the proposed simulation with a real video clip.
The third paper, by Oleg Burdakov and Oleg Sysoev, presents the development of an active-set algorithm based on duality for solving a special regularized slope-constrained monotonic regression problem. The authors show competitive complexity results both theoretically and in practice, while illustrating desirable features of the obtained solutions.
The fourth paper by Fateme Kouchakinejad and Alexandra Šipošová is concerned with the notion of ordered weighted averaging operators and gives a review of their applications in decision making. The authors also give some generalizations of the operators along with illustrative examples.
The last three articles are concerned with certain applied problems in Sweden, Netherlands and Oman.
As the fifth paper, Peter Lohmander presents some results for a stochastic optimal control approach to the management of the wildlife. The author first derives general optimal control and value functions, and then makes use of relevant functions for the moose management in Sweden.
Cornelis Roos discusses a mathematical model developed for protecting the Netherlands from possible incurring flood damages. The author has been seriously involved with the development of the model in the past decade and has been shown to be successful in using the model in the Netherlands to set up legal safety standards in the country.
Finally, Chefi Triki, Abdulwahab Al-Maimani and Jamila Akil propose a ridesharing model for use in Muscat, Oman, to control the growing traffic congestion in the city. They provide a detection support system for the model. The set of feasible routes of the ridesharing is found by solving a constrained mathematical programming problem. Then, a bin packing problem is modelled and solved to find the optimal routes. Illustrative examples are worked through.

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This is a special issue of the Iranian Journal of Operations Research that includes some of the
invited talks presented at the 11th international conference of the Iranian Operations Research Society
(IORS), organized jointly by IORS and Razi University of Kermanshah and held at the Razi
University, Kermanshah, Iran, May 2-4, 2018. The IORS conference is held annually and is the main
event for presentation of new theoretical and applied developments of OR. International participation
is enhanced by some invited talks presented by international scholars. There were over 400
participants, 170 accepted talks and 69 poster presentations. The selected papers for this special issue
were reviewed going through the usual reviewing process and 6 papers were accepted for publication.

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Over the past few decades, there has been a growing need to address the limitations of the Data Envelopment Analysis methodology, particularly the issue of freely selecting weights. As a result, common weight models have emerged and expanded. This article aims to provide a comprehensive overview of CSW methods, analyzing papers and bibliometric information through a systematic literature review. In this study, a total of 116 articles on CSW published between 1991 and 2022 were carefully selected and reviewed. These contributions were categorized based on specific features related to the computational technique or the main purpose of the procedure. The findings revealed that uncertain models had the highest share among the articles in the field of CSW. Furthermore, the Journal of Expert Systems with Applications emerged as the leading journal in terms of the number of publications on CSW models in DEA. The analysis of the bibliometric information of the articles was carried out using advanced software tools, including R-Studio and VOS Viewer... This review offers valuable insights and discussion, which can guide future research endeavors in this field. By addressing the limitations of DEA and exploring various CSW methods, this study contributes to the advancement of knowledge and understanding in this area.
 

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       A transportation problem involving three constraints: source, destination, and conveyance, where all parameters of the problem are fuzzy is called Fully Fuzzy Solid Transportation Problem (FFSTP). In this paper, a new method is proposed to find an optimal solution of an unbalanced FFSTP which the fuzzy numbers are considered to be k-scale trapezoidal fuzzy numbers. The k-scale trapezoidal fuzzy numbers are a generalization of symmetric trapezoidal fuzzy numbers which are considered recently in the literature. In this method, using a new ranking method, we transform the unbalanced FFSTP into a crisp linear programming formulation and find a fuzzy optimal solution for it. The considered model is not necessary balanced and introduced method will solve that without convert it to a balanced model. The advantages of the proposed method are also discussed.
 

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One of the most important and widely used problems in the logistics part ‎of ‎any supply chain is the location-routing problem (LRP) of vehicles. The ‎‎purpose is to select distribution centers to supply goods for ‎‎customers and create suitable travel routes for vehicles to serve ‎customers.‎ Studies conducted in the field of supply chain logistics systems have shown that if vehicle travel routing is neglected when locating supply centers, the costs of the logistics system may increase dramatically. Therefore, in the LRP problem, the location of supply centers and the routing of vehicles are considered simultaneously. In this paper, we will present a multi-objective model for vehicle location-routing problems with a flexible fuzzy ‎approach. Its' goals are to make strategic decisions to deploy ‎candidate supply centers at the beginning of the planning horizon, as well as ‎form the vehicle travel at the tactical level to serve the customers in ‎short-term periods of time. Therefore, in ‎order to adapt the mathematical model to the real conditions, the ‎constraints related to the capacity of the vehicles have been considered in a ‎flexible fuzzy state, and also the problem has been modeled in a multi-period state along with the presence of the distance limit and the ‎accessibility factor for each vehicle. The evaluation criterion is to minimize costs related to the establishment of candidate supply centers, the fixed cost of using vehicles and transportation costs, as well as maximizing customer satisfaction by reducing shortage costs and reducing harmful environmental effects. To solve the model, it is first converted into a single-objective model using the weight method and then solved using the proposed algorithm. Finally, using a numerical example in the field of waste management, the effectiveness of the proposed solution method is shown. It should be mentioned that the model was solved using GAMS software and the results are shown.
 

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The main objective of this study is to identify and rank foreign investment risk factors and determine their impact on attracting foreign investment in the upstream oil industries. In terms of nature and method, it is descriptive and, in terms of relationships, it is inferential and correlational. The statistical population of the research includes managers and experts in the upstream oil industries, and the sample size was estimated to be 103 people using random sampling. The collected data was analyzed using SPSS, Expert Choice, and Smart PLS software. The results showed that according to the experts in the statistical population, economic risk is the most important factor in foreign investment. Also, in the structural equation modeling method, the correlation between foreign investment risk and attraction factors was significant, with political risk having the greatest impact on foreign investment risk, followed by economic and financial risks and 87.4% of the changes in foreign investment attraction factors could be predicted by foreign investment risk, and the overall fit of the proposed model showed a GOF value of 0.447, indicating a high fit of the research model.

 

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Background & Aim: Management style in medical care is very important in the guidance and performance of the treatment team. This is effective in improving the quality and reducing the treatment time and increasing the productivity of organizations. Using different management styles in organizations will lead to different results in employee performance and organizational productivity. The present study was conducted to determine the relationship between management styles and organizational productivity in the Children's Medical Center of Tehran University of Medical Sciences.
Methods & Materials: This study is predictive correlational in nature. It was conducted on 112 nurses and managers working in the treatment department who were selected based on the random sampling method from. The data were analyzed through conducting ANOVA, t-test, Pearson correlation, and linear regression analysis in SPSS version 16.
Results: The mean score of applying authoritarian style was 4.54, consultative style 5.54, collaborative style 5.55, relational style 5.64 and transformational style 5.59. There was a statistically significant and direct relationship between management style and organizational productivity (p<0.05), (r=0.760). The determination coefficient of linear regression modeling was used to predict the changes in organizational productivity based on the management style indicated that 87.2% of the changes in organizational productivity was explained under the influence of independent variables.
Conclusion: Due to the direct relationship between the use of management styles and organizational productivity, it is not possible to use one style in organizations and the use of different styles in different departments will improve the productivity of the organization.
Background & Aim: Management style in medical care is very important in the guidance and performance of the treatment team. This is effective in improving the quality and reducing the treatment time and increasing the productivity of organizations. Using different management styles in organizations will lead to different results in employee performance and organizational productivity. The present study was conducted to determine the relationship between management styles and organizational productivity in the Children's Medical Center of Tehran University of Medical Sciences.
Methods & Materials: This study is predictive correlational in nature. It was conducted on 112 nurses and managers working in the treatment department who were selected based on the random sampling method from. The data were analyzed through conducting ANOVA, t-test, Pearson correlation, and linear regression analysis in SPSS version 16.
Results: The mean score of applying authoritarian style was 4.54, consultative style 5.54, collaborative style 5.55, relational style 5.64 and transformational style 5.59. There was a statistically significant and direct relationship between management style and organizational productivity (p<0.05), (r=0.760). The determination coefficient of linear regression modeling was used to predict the changes in organizational productivity based on the management style indicated that 87.2% of the changes in organizational productivity was explained under the influence of independent variables.
Conclusion: Due to the direct relationship between the use of management styles and organizational productivity, it is not possible to use one style in organizations and the use of different styles in different departments will improve the productivity of the organization.
 

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With the expansion of emerging technologies, their applications have been introduced as a transformative factor in many industries and fields. However, these developments require more research in the area of new technologies. Nevertheless, few studies have comprehensively examined the published research in this field. In this regard, bibliometric studies, as one of the effective research methods in the field of emerging technologies, are a practical and effective tool in identifying research patterns, knowledge flows, study content, and key terms. Using this method, one can understand and briefly examine the scientific foundations and impact of emerging technologies. In summary, conducting bibliometrics in the field of emerging technologies can be used as an effective tool in identifying and analyzing research paths and the development of advanced technologies. In this context, articles published in the field of emerging technologies in the period 2013-2023 in various fields have been examined. The required data includes 13,263 articles extracted from the WOS database and were analyzed using Biblioshiny software under R-package. The obtained results include identifying influential authors, leading journals, organizations, and countries related to the field of emerging technologies. Additionally, using precise bibliometric analysis tools, the authors' collaboration network, thematic trends, most common terms, and citation network have been extracted. Finally, with the help of network analysis, key clusters in the existing literature have been identified based on research areas of new technologies.