Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
6
1
2012
04
01
A Model for Runway Landing Flow and Capacity with Risk and Cost Benefit Factors
1
19
EN
Babak
Ghalebsaz Jeddi
Dept. of Industrial Engineering, Sharif University of Technology, Tehran, Zip 14588,Iran
John F.
Shortle
Dept. of Systems Engineering and Operations Research, George Mason University, Fairfax, VA22030, USA
As the demand for the civil aviation has been growing for decades and the system becoming increasingly complex, the use of systems engineering and operations research tools have shown to be of further use in managing this system. In this study, we apply such tools in managing landing operations on runways (as the bottleneck and highly valuable resources of air transportation networks) to handle its optimal and safe usage. We consider a uniform aircraft fleet mix landing on a runway with two major landing risks of wake-vortex encounter and simultaneous runway occupancy. Here, we empirically estimate minimum safe wake-vortex separation thresholds, extend go-around procedure to avoid wake-vortex encounter, and enforce the go-arounds assumed to be risk free. We introduce cost-benefit factors to study implications of enforced go-arounds, and develop models to adjust the average separation to maximize the net economic outcome. This also estimates the runwayâ€™s true landing capacity, and provides a ground for quantifying effect of separation variance on optimal throughput. An estimation of the economic effect of wake-vortex phenomenon is also presented. Illustrations are provided through real world data.
Aircraft separation,Landing safety,safety,Wake-vortex,Landing capacity,Goaround
procedure,Variance reduction,Cost and benefit analysis
http://www.jise.ir/article_4055.html
http://www.jise.ir/article_4055_45d1edffd19bc033fcb1a6aac82d0607.pdf
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
6
1
2012
04
01
A Comparison of Four Multi-Objective Meta-Heuristics for a Capacitated Location-Routing Problem
20
33
EN
Farshid
Samaei
Department of Industrial Engineering, Shahed University, Tehran, Iran
Mahdi
Bashiri
Department of Industrial Engineering, Shahed University, Tehran, Iran
Reza
Tavakkoli-Moghaddam
Departmentof Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
In this paper, we study an integrated logistic system where the optimal location of depots and vehicles routing are considered simultaneously. This paper presents a new mathematical model for a multi-objective capacitated location-routing problem with a new set of objectives consisting of the summation of economic costs, summation of social risks and demand satisfaction score. A new multi-objective adaptative simulated annealing (MOASA) is proposed to obtain the Pareto solution set of the presented model according to the previous studies. We also apply three multi-objective meta-heuristic algorithms, namely MOSA, MOTS and MOAMP, on the simulated data in order to compare the proposed procedure performance. The computational results show that our proposed MOASA outperforms the three foregoing algorithms.
Location-routing problem,Demand satisfaction score,Multi-objective metaheuristic
algorithms,Pareto solution set
http://www.jise.ir/article_4056.html
http://www.jise.ir/article_4056_fe2ace436cf9be17c5252d9557e94e61.pdf
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
6
1
2012
04
01
A Fuzzy Random Minimum Cost Network Flow Programming Problem
34
47
EN
Javad
Nematian
Department of Industrial Engineering, University of Tabriz, Iran
Kourosh
Eshghi
Department of Systems Engineering, Sharif University of Technology, Tehran, Iran
eshghi@sharif.edu
In this paper, a fuzzy random minimum cost flow problem is presented. In this problem, cost parameters and decision variables are fuzzy random variables and fuzzy numbers respectively. The object of the problem is to find optimal flows of a capacitated network. Then, two algorithms are developed to solve the problem based on Er-expected value of fuzzy random variables and chance-constrained programming. Furthermore, the results of two algorithms will be compared. An illustrative example is also provided to clarify the concept.
network flow programming,fuzzy random variable,Er-expected value,chanceconstrained
programming
http://www.jise.ir/article_4057.html
http://www.jise.ir/article_4057_ea9d514e9bf31829c10b874267b35c8b.pdf
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
6
1
2012
04
01
The P-Center Problem under Uncertainty
48
57
EN
Majid
Taghavi
Dept. of Industrial Engineering, Sharif University of Technology, Tehran, Iran
Hassan
Shavandi
Dept. of Industrial Engineering, Sharif University of Technology, Tehran, Iran
shavandi@sharif.edu
Facility location decisions play a prominent role in strategic planning of many firms, companies and governmental organizations. Since in many real-world facility location problems, the data are subject to uncertainty, in this paper, we consider the P-center problem under uncertainty of demands. Using Bertsimas and Sim approach, we develop a robust model of the problem as an integer programming model. Furthermore, we develop a tabu search algorithm for solving the problem. Finally we use design of experiments (DOE) to adjust the parameters of tabu search algorithm. The numerical results of algorithm are presented accordingly.
Facility location,robust optimization,P-Center,Tabu Search
http://www.jise.ir/article_4058.html
http://www.jise.ir/article_4058_f386294adb4353323a811ed9f2e06648.pdf