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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.