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  A fuzzy goal programming-based approach is used to solve a proposed multi-objective linear programming model and simultaneously handle two important problems in cellular manufacturing systems, viz. cell formation and layout design. Considerations of intra-cell layout, the intra-cell material handling can be calculated exactly. The advantages of the proposed model are considering machining cost, inter-cell, intra-cell (forward and backward) material handling, operation sequence and resource constraints on the capacity of machines. To illustrate applicability of the proposed model, an example is solved and computational results are noted.

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A number of problems in several areas such as power transmission and distribution, communication and transportation can be formulated as a stochastic-flow network (SFN). The system reliability of an SFN can be computed in terms of all the upper boundary points, called d-MinCuts (d-MCs). Several algorithms have been proposed to find all the d-MCs in an SFN. Here, some recent studies in the literature on search for all d-MCs are investigated. We show that some existing results and the corresponding algorithms are incorrect. Then, correct versions of the results are established. By modifying an incorrect algorithm, we also propose an improved algorithm. In addition, complexity results on a number of studies are shown to be erroneous and correct counts are provided. Finally, we present comparative numerical results in the sense of performance profile of Dolan and Moré showing the proposed algorithm to be more efficient than some existing algorithms.

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Over five decades have passed since the first wave of robust optimization studies conducted by Soyster and Falk. It is outstanding that real-life applications of robust optimization are still swept aside; there is much more potential for investigating the exact nature of uncertainties to obtain intelligent robust models. For this purpose, in this study, we investigate a more refined description of the uncertain events including (1) event-driven and (2) attribute-driven. Classical methods transform convex programming classes of uncertainty sets. The structural properties of uncertain events are analyzed to obtain a more refined description of the uncertainty polytopes. Hence, tractable robust models with a decent degree of conservatism are introduced to avoid the over-protection induced by classical uncertainty sets.

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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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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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Here, a new mathematical model for cellular manufacturing systems considering three important features of part priority, levels of machine’s technology, and the operator’s skill is developed. Simultaneous consideration of these features provides a more realistic analysis of the problems in cellular manufacturing systems. A model with multiple design features including cell formation, human resources flexibility with different skills, machines flexibility, operational sequence, processing time, and the capacity of machine and manpower is proposed in this article. Ourfocus is on the design of cells to implementtwo dissimilar goals. The first goal is the reduction of inter-cellular movements of parts and workers. The second goal is the creation of efficient cellsby making cell’s quality level identical for produced products so that the production of all the different parts have good quality. Two approaches of augmented ε-constraint and non-dominated sorting genetic algorithm II (NSGA-II) are used to solve this model. By comparison of these two approaches, we realizethat the multi-objective evolutionary optimization algorithm creates a Pareto-optimal front in a reasonable amount of time forlarge-scale problems