Iranian Journal Of Operations Research
Volume:8 Issue: 2, Summer and Autumn 2017

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.

Clustering problems with the similarity measure defined by the $𝐿_1$-norm are studied. Characterizations of different stationary points of these problems are given using their difference of convex representations. An algorithm for finding the Clarke stationary points of the clustering problems is designed and a clustering algorithm is developed based on it. The clustering algorithm finds a center of a data set at the first iteration and gradually adds one cluster center at each consecutive iteration. The proposed algorithm is tested using large real world data sets and compared with other clustering algorithms.

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.

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.

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.

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.

Many regions in the world are protected against flooding by a dike, which may be either natural or artificial. We deal with a model for finding the optimal heights of such a dike in the future. It minimizes the sum of the investments costs for upgrading the dike in the future and the expected costs due to flooding. The model is highly nonlinear, nonconvex, and infinite-dimensional. Despite this, the model can be solved analytically if there is no backlog in maintenance. If there is a backlog in maintenance, then the optimal solution can be found by minimizing a convex function over a finite interval. However, if the backlog becomes extremely large we show that the model breaks down. Our model has been used in The Netherlands to define legal safety standards for the coming decades.

We deal with developing a Decision Support System (DSS) to promote the ridesharing among both students and staff of a big organization. The DSS includes a set of functions that allow the management of the riders’ requests and drivers’ availability and embeds a novel two-phase optimization approach that helps in defining the optimal riders-drivers matching. The first phase consists of solving a constraint programming model that generates all the feasible routes. Then, the second phase a bin packing based model is solved to find the optimal route for every driver in order to serve the set of riders assigned to her vehicle. We conclude by an illustrative example that shows the validity of our DSS and, finally, by a discussion on the possible commercialization of such a platform.