دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
20
3
2023
9
1
Developing a Stochastic Bi-Objective Inventory Control Model through Packing Ordering System and a Multi-level Distribution based on Bin Packaging Problem
1
17
FA
S. M.
Tahanian Qomi
Department of Industrial Engineering, Payam Noor University, Tehran, Iran
masoudtahanian66@gmail.com
N
M.
Hamedi
Department of Industrial Engineering, Payam Noor University, Tehran, Iran
maryam.hamedi@gmail.com
Y
R.
Tavakkoli Moghaddam
Industrial Engineering Department, Tehran University, Tehran, Iran
tavakoli@ut.ac.ir
N
10.22034/20.3.1
This paper develops a stochastic bi-objective inventory control model, in which the demand with the lead time is a random variable as a normal distribution. It uses a multi-mode distribution, in which each distributer has own selling price and batch size. The retailer should order his/her demand in differnet batch sizes and a minimum order quantity. Bin packing problems have been used for allocation oders to distribution, which belong to a class of well-studied and highly popular combinatorial optimization problems. In general, they are motivated by a large number of real-world applications. Because the presented model is a bi-objective nonlinear programming type and NP-hard one to be solved in a reasonable time, a well-known multi-objective evolutionary algorithm, namely a non-dominated sorting genetic algorithm (NSGA-II), is proposed. To verify the obtained solution and evaluate the performance of the NSGA-II, the ε-constraint method is developed in solving small-sized problems. In large-sized problems, the test problems are solved by the proposed NSGA-II. Then, the Pareto-optimal solutions are evaluated by mean ideal distance, diversitificatiom and time metrics.
Multi-Mode Distribution, Batch Ordering, Multi Objective Optimization
http://jamlu.liau.ac.ir/article-1-1795-en.html
http://jamlu.liau.ac.ir/article-1-1795-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
20
3
2023
9
1
The Recovery of Sparse Signals by Sequential Quadratic Programming Approach
19
32
FA
M. S.
Alamdari
Department of Mathematics, K. N. Toosi University of Technology, Teharn, Iran
m.s.alamdari69@gmail.com
Y
M.
Fatemi
Department of Mathematics, K. N. Toosi University of Technology, Teharn, Iran
m.s.alamdari2000@gmail.com
N
A.
Ghaffari
Department of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran
m.s.alamdari@email.kntu.ac.ir
N
10.22034/20.3.19
In this article, with the idea of the sequential quadratic programming method and using the smoothed l0 norm as the objective function, a modified sequential quadratic programming method is presented to solve the problem of finding sparse solutions of the system of underdetermined linear equations. We provide a new approach for solving quadratic subproblems, which leads to the less complexity and simplicity in solving quadratic subproblems. The proposed method starts with an initial guess and in each iteration to calculate the search direction, a specific quadratic optimization problem is solved. The quadratic approximation of the objective function and the linear approximation of the constraints of the original problem are used to design the subproblem. Then, theoretical analysis of the method is presented and its convergence is proved. The results obtained from the implementation of the proposed method on sensor matrices of different dimensions show that the efficiency of the method does not depend on the dimensions of the input matrix. Finally, the comparison of the reported SNR regarding to the proposed method with the most frequent thin signal recovery algorithms shows the high efficiency and performance of the proposed method.
Sparse Signal Recovery, Nonlinear Programming, Smoothed Norm, Sequential Quadratic Programming
http://jamlu.liau.ac.ir/article-1-2174-en.html
http://jamlu.liau.ac.ir/article-1-2174-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
20
3
2023
9
1
A Lagrangian Relaxation Algorithm for Integrated Resource-Constrained Multi-Project Scheduling and Material Ordering and Production Planning Problem
33
60
FA
A.
Parchami Afra
Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran
aliparchami@ut.ac.ir
N
A. S.
Kheirkhah
Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran
kheirkhah@basu.ac.ir
Y
10.22034/20.3.33
Resource-constrained project scheduling is one of the well-known problem in project management The integration of project scheduling, material ordering, and production planning of non-renewable resources leads to the coordination of project implementation and supplying resources. This coordination reduces total costs, including operating activities, production, ordering, holding, and penalty costs for late project completion. In this paper, a mixed integer programming model is presented for the resource-constrained multi-project scheduling problem and material ordering and production planning. The integrated mathematical model determines the decisions regarding the start time of activities, the quantity and time of materials ordering, and the production planning of suppliers. Due to the application of Lagrangian Relaxation algorithm in solving complex problems, this algorithm has been used to solve the proposed mathematical model. As a heuristic algorithm, the feasiblizer algorithm is also proposed for feasibilization of the solution obtained from the Lagrange Relaxation algorithm. To evaluate the performance of the proposed model and solution method, a set of sample examples is solved and the numerical results are given. The findings of this paper show the good performance of the model and the solution method and can provide managerial insights for project managers and resource suppliers.
Resource-Constrained Multi Project Scheduling, Material Procurement, Material Ordering, Production Planning, Lagrangian Relaxation Algorithm
http://jamlu.liau.ac.ir/article-1-2170-en.html
http://jamlu.liau.ac.ir/article-1-2170-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
20
3
2023
9
1
Analysis of Environmental Pollution and Its Effects on Health, Application of DFM-Based Non-Radial Modeling
61
86
FA
F.
Zamzam
Management Department, Yazd University, Yazd, Iran
Fateme.zmzm@stu.yazd.ac.ir
N
H.
Zare ahmadabadi
Management Department, Yazd University, Yazd, Iran
Zarehabib@yazd.ac.ir
Y
A.
Naser Sadrabadi
Management Department, Yazd University, Yazd, Iran
alireza_naser@yazd.ac.ir
N
A.
Morovati Sharifabadi
Management Department, Yazd University, Yazd, Iran
alimorovati@yazd.ac.ir
N
10.22034/20.3.61
Analyzing the efficiency of countries in the field of sustainable development, especially with focus on the effect of greenhouse gas emissions and air pollutants on human health, can be very useful for regional and global development policymaking. This study evaluates the performance of 38 OECD countries by providing a DFM model. Comparing the changes in the rate of increase in output and the rate of decrease in inputs for the efficiency of decision units in DFM and CCR models is one of the objectives of this study. This research is applied research in terms of purpose and is descriptive research in terms of implementation. According to the review of the literature and research background of CO2 emissions, NOx emissions, SO2 emissions, health expenditure and heavy metals as input, and air quality indicators based on environmental performance index (EPI) report such as PMW, PME and HAD been considered as output. The results showed that inefficient countries should make the most change in the input variables such as CO2 emissions, NOx emissions, SO2 emissions in order to reach the efficiency frontier; therefore, paying attention to the management and control of greenhouse gas emissions and air pollutants can be effective in changing inefficient countries with poor performance in environmental sustainability. The analysis also showed that in order to improve the sustainability in inefficient countries, policymakers should pay close attention to reducing and controlling CO2 emissions, NOx emissions and SO2 emissions, and to discuss specific budget allocations for the prevention and treatment of air pollution-related diseases. According to the research method, two modeling methods of evaluating the efficiency of countries in the field of sustainable development were compared and the advantages of DFM model in comparison to CCR were studied.
Performance Evaluation, Data Envelopment Analysis (DEA), Environmental Sustainability, Distance Friction Minimization (DFM), Health
http://jamlu.liau.ac.ir/article-1-2147-en.html
http://jamlu.liau.ac.ir/article-1-2147-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
20
3
2023
9
1
An Online Supervised Machine Learning Algorithm to Solve a Bi-Level Network Design Problem
87
107
FA
M.
Sadra
Mathematics and Computer Sciences Department, Hakim Sabzevari University, Sabzevar, Iran
mahmoodsadra@gmail.com
N
M.
Zaferanieh
Mathematics and Computer Sciences Department, Hakim Sabzevari University, Sabzevar, Iran
mehdi.zaferanieh@gmail.com
Y
10.22034/20.3.87
This paper investigates a bi-level network design problem and proposes a hybrid optimization-machine learning algorithm to solve it. Bi-level problems are typically NP-hard, and even in the simplest scenario where both upper and lower level problems are linear, they remain NP-hard. Machine learning methods have gained popularity in recent years due to their accuracy and reasonable running time. In this study, we apply a hybrid optimization-machine learning algorithm using an online learning method to solve the proposed bi-level network design problem. Our primary objective is to select a set of candidate edges that minimize traffic flow as much as possible. The upper-level objective function aims to minimize the average total travel time and fixed cost expenses required to establish the newly designed edges. Meanwhile, the lower-level objective function focuses on minimizing individual travel time from the viewpoint of users. We provide several numerical examples to demonstrate the effectiveness of our proposed model and its hybrid solution approach.
Bi-Level Programming, Supervised Machine Learning, Traffic Assignment Problem, Network Design Problem
http://jamlu.liau.ac.ir/article-1-2146-en.html
http://jamlu.liau.ac.ir/article-1-2146-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
20
3
2023
9
1
A New DEA Model in the Presence of Flexible Measures with Flexible Value Based on Piecewise Linear Theory
109
121
FA
N.
Roudabr
Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
nasim.roudabr@srbiau.ac.ir
N
Esmaeil
Najafi
Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
e.najafi@srbiau.ac.ir
Y
Z.
Moghaddas
Department of Mathematics and Statistics, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Zmoghaddas@qiau.ac.ir
N
F.
Movahedi Sobhani
Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Fmovahedi@iau.ac.ir
N
10.22034/20.3.109
In real problems, the nature of some factors is not precisely known, and they can be considered as both input and output, which they are called flexible measures. In the proposed models, for evaluating the performance of decision making units (DMUs) with flexible measures, the value of the variables is considered linear. While in real issues many inputs and outputs of DMUs, including flexible variables have nonlinear values. In other words, if the flexible measure is considered as input, its valuation will be decreasing, and if it is considered as output, its valuation will be increasing (for desirable output). In fact, decision makers seek to maximize output and minimize inputs, therefore, in calculating efficiency and also differentiating between DMUs, less value should be considered for higher amount of inputs and more value for higher amount outputs. Several DMUs may be efficient, but one of them consumes less input than other efficient DMUs to maximize output, so according to the model presented in this article, it will get a higher rank in the ranking of DMUs. So, this paper proposes a new model to evaluate performance based on data envelopment analysis (DEA) and a piecewise linear function in the presence of flexible variables which considers the different effect of flexible variables in efficiency evaluation and distinguishes the valuation between flexible variables as inputs and outputs. The proposed model is used to evaluate the efficiency of cement factories listed on the stock exchange.
DEA, Flexible Measure, Nonlinear Value, Piecewise Linear Function.
http://jamlu.liau.ac.ir/article-1-2083-en.html
http://jamlu.liau.ac.ir/article-1-2083-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
20
3
2023
9
1
Presenting a New Method of Electromagnetic Field Algorithm Inspired by Quantum Theory to Solve Static One-Objective Optimization Problem
123
139
FA
A.
Taqaddosi
Department of Information Technology Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran
a.taghaddosi@gmail.com
N
M.
Afshar Kazemi
Department of Industrial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran
M_afsharkazemi@iauec.ac.ir
Y
A.
Sharifi
Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
a.sharifi@srbiau.ac.ir
N
M.
Keramati
Department of Industrial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran
m.keramati@gmail.com
N
A.
Daneshvar
Department of Information Technology Management, Electronic Branch, Islamic Azad University, Tehran, Iran
a_daneshvar@iauec.ac.ir
N
10.22034/20.3.123
In this research, a new method of quantum-inspired electromagnetic field algorithm is proposed to solve optimization problems. The electromagnetic field algorithm simulates the mechanism of absorption and repulsion between electromagnetic particles with different poles. The main idea of this algorithm is to guide the electromagnetic particles to the global optimum by the forces of attraction and repulsion and the golden ratio. In the proposed algorithm, inspired by the quantum concepts and test charge strategy, changes have been made in the basic algorithm, which has led to improved performance of this algorithm. In the proposed algorithm, the concept of qubit is used and some of the particles are affected by the mutation using a quantum gate. Experimental results on 10 different standard functions show that the proposed algorithm has better performance than the basic algorithm and other proposed algorithms.
Static One-Objective Optimization, Meta-heuristic Algorithm, Electromagnetic Field Algorithm, Quantum Theory
http://jamlu.liau.ac.ir/article-1-2088-en.html
http://jamlu.liau.ac.ir/article-1-2088-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
20
3
2023
9
1
Providing a Product Life Cycle Optimization Using Agent Based Modeling Simulation
141
160
FA
M.
Farahbakhsh
Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran , Iran
mohammad.farahbakhsh@srbiau.ac.ir
N
M.
Modiri
Department of Industrial Management, South Tehran Branch, Islamic Azad University, Tehran, Iran
m_modiri@azad.ac.ir
Y
M.
Khatami FirozAbadi
Department of Industrial Management, Allameh Tabataba'i University, Tehran, Iran
a.khatami@aut.ac.ir
N
A.
Pourebrahimi
Department of Industrial Management, Karaj Branch, Islamic Azad University, Alborz, Iran
poorebrahimi@gmail.com
N
10.22034/20.3.141
With increasing competition in global markets, organizations are paying more attention to the life cycle of their products. To achieve this goal, it is necessary to decide on the studies conducted in the product life cycle, and the more factors are considered, the better the result. Therefore, in this research, an attempt has been made to provide a life cycle optimization model for the electricity industry. In this model, consumer, producer, government, capital and technology factors are considered for simulation, with the help of which you try to study the process of electricity generation and build this process according to the amount of consumption and technology, as well as use. Among them is the reduction of carbon dioxide emissions and their effects on the environment. To analyze the results and optimize the model, the Anylogic software was taken, which was implemented after the implementation of the model to optimize the results of the scenario according to the opinions of experts and the final result was obtained. According to the studies performed from the optimization model presented with the actual results in the results between 2011 to 2019 was consistent with a small distance, which indicates a high validity of the model, also to optimize the model to reduce air and reduce Carbon emissions reduced fossil fuel consumption by changing the technology factor, resulting in a significant reduction in air consumption.
Product Life Cycle, Optimization, Agent Based Modelling Simulation (ABMS), Electricity Industry
http://jamlu.liau.ac.ir/article-1-2128-en.html
http://jamlu.liau.ac.ir/article-1-2128-en.pdf