Open Journal of Optimization

Journal Information
ISSN / EISSN : 23257105 / 23257091
Current Publisher: Scientific Research Publishing, Inc. (10.4236)
Total articles ≅ 90
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Latest articles in this journal

Fulgence Nahayo, Salah Khardi
Open Journal of Optimization, Volume 9, pp 15-26; doi:10.4236/ojop.2020.92002

The aim of this paper is to set up an efficient nonlinear application algorithm predictive model for a multi aircraft landing dynamic system called “Aircraft Landing Dynamic System, Release 2019A+ version “AIRLADYS R2019A+”. This programming software combines dynamic programming technic for mathematical computing and optimisation run under AMPL and KNITRO Solver. It uses also a descriptive programming technic for software design. The user interfaces designed in Glade are saved as XML, and by using the GtkBuilder GTK+ object these can be loaded by applications dynamically as needed. By using GtkBuilder, Glade XML files can be used in numerous programming languages including C, C++, C#, Java, Perl, Python, AMPL, etc. Glade is Free Software released under the GNU GPL License. By these tools, the solved problem is a mathematical modelization problem as a non-convex optimal control governed by ordinary non-linear differential equations. The dynamic programming technic is applied because it is a sufficiently high order and it does not require computation of the partial derivatives of the aircraft dynamic. This application will be coded with Linux system on 64 bit operating system, but it can also be run on the windows system. High running performances are obtained with results giving feasible trajectories with a robust optimizing of the objective function.
Abdulhadi Altherwi, Mohamed Zohdy
Open Journal of Optimization, Volume 9, pp 1-14; doi:10.4236/ojop.2020.91001

This paper aims at investigating the optimization of supply chain networks (SCN) for industrial plants under vendor managed inventory (VMI) policy. The vendor uses Long Range Wide Area Network (LoRaWAN) to minimize the total cost of networks. The problem was developed as a mixed-integer non-linear program (MINLP) model, which helped in reducing the total cost of a VMI, to formulate the coordinated decision issue that incorporates the location inventory issue with the allocation task of LoRaWAN technology and its level of investment. We performed different strategies of investment of LoRaWAN technology of having objective function with three different scenarios: 1) Investment of LoRaWAN technology only in ordering operations; 2) Investment of LoRaWAN technology only in holding operations; 3) Investment of LoRaWAN technology in both holding and ordering operations. The simulation results indicated that the cost-saving obtained by the third scenario is significant due to the least total cost of the objective function as compared with the total cost of the objective function obtained by the first and second scenarios.
Saba M. Alwan, Abdo M. Al-Mahdi, Omalsad H. Odhah
Open Journal of Optimization, Volume 9, pp 71-85; doi:10.4236/ojop.2020.93006

Optimal control is one of the most popular decision-making tools recently in many researches and in many areas. The Lorenz-Rössler model is one of the interesting models because of the idea of consolidation of the two models: Lorenz and össler. This paper discusses the Lorenz-Rössler model from the bifurcation phenomena and the optimal control problem (OCP). The bifurcation property at the system equilibrium is studied and it is found that saddle-node and Hopf bifurcations can be holed under some conditions on the parameters. Also, the problem of the optimal control of Lorenz-Rössler model is discussed and it uses the Pontryagin’s Maximum Principle (PMP) to derive the optimal control inputs that achieve the optimal trajectory. Numerical examples and solutions for bifurcation cases and the optimal controlled system are carried out and shown graphically to show the effectiveness of the used procedure.
Martin M. Kasina, Koske Joseph, Mutiso John
Open Journal of Optimization, Volume 9, pp 47-70; doi:10.4236/ojop.2020.93005

Tahmineh Azizi, Bacim Alali
Open Journal of Optimization, Volume 9, pp 86-104; doi:10.4236/ojop.2020.93007

In the current work, we study two infectious disease models and we use nonlinear optimization and optimal control theory which helps to find strategies towards transmission control and to forecast the international spread of the infectious diseases. The relationship between epidemiology, mathematical modeling and computational tools lets us to build and test theories on the development and fighting with a disease. This study is motivated by the study of epidemiological models applied to infectious diseases in an optimal control perspective. We use the numerical methods to display the solutions of the optimal control problems to find the effect of vaccination on these models. Finally, global sensitivity analysis LHS Monte Carlo method using Partial Rank Correlation Coefficient (PRCC) has been performed to investigate the key parameters in model equations. This present work will advance the understanding about the spread of infectious diseases and lead to novel conceptual understanding for spread of them.
Huaxu Dan
Open Journal of Optimization, Volume 9, pp 39-46; doi:10.4236/ojop.2020.93004

A two-dimensional horn antenna is used as a model for topology optimization. In order to employ the topology optimization, each point in the domain is controlled by a function which is allowed to take values between 0 and 1. Each point’s distinct value then gives it an effective permittivity, either close to that of polyimide or that of air, two materials considered in this study. With these settings, the optimization problem becomes finding the optimal distribution of materials in a given domain, and is solved under constraints of reflection and material usage by the Method of Moving Asymptotes. The final configuration consists of two concentric arcs of air while polyimide takes up the rest of the domain, a result relatively unsensitive to the choice of constraints and initial values. Compared to the unoptimized antenna, a slimmer main lobe is observed and the gain boosts.
Munir Hossain, Mollah Mesbahuddin Ahmed, Amirul Islam, Shirajul Islam Ukil
Open Journal of Optimization, Volume 9, pp 27-37; doi:10.4236/ojop.2020.92003

Transportation of products from sources to destinations with minimal total cost plays an important role in logistics and supply chain management. In this article, a new and effective algorithm is introduced for finding an initial basic feasible solution of a balanced transportation problem. Number of numerical illustration is introduced and optimality of the result is also checked. Comparison of findings obtained by the new heuristic and the existing heuristics show that the method presented herein gives a better result.
Abdulazeez Bilesanmi, Ashiribo Senapon Wusu, Akinwale Lewis Olutimo
Open Journal of Optimization, Volume 8, pp 32-37; doi:10.4236/ojop.2019.81003

In this paper, we approach the problem of obtaining approximate solution of second-order initial value problems by converting it to an optimization problem. It is assumed that the solution can be approximated by a polynomial. The coefficients of the polynomial are then optimized using simulated annealing technique. Numerical examples with good results show the accuracy of the proposed approach compared with some existing methods.
Harrison Obiora Amuji, Etus Chukwuemeka, Emeka Maxwel Ogbuagu
Open Journal of Optimization, Volume 8, pp 15-31; doi:10.4236/ojop.2019.81002

Fraud is a major challenge facing telecommunication industry. A huge amount of revenues are lost to these fraudsters who have developed different techniques and strategies to defraud the service providers. For any service provider to remain in the industry, the expected loss from the activities of these fraudsters should be highly minimized if not eliminated completely. But due to the nature of huge data and millions of subscribers involved, it becomes very difficult to detect this group of people. For this purpose, there is a need for optimal classifier and predictive probability model that can capture both the present and past history of the subscribers and classify them accordingly. In this paper, we have developed some predictive models and an optimal classifier. We simulated a sample of eighty (80) subscribers: their number of calls and the duration of the calls and categorized it into four sub-samples with sample size of twenty (20) each. We obtained the prior and posterior probabilities of the groups. We group these posterior probability distributions into two sample multivariate data with two variates each. We develop linear classifier that discriminates between the genuine subscribers and fraudulent subscribers. The optimal classifier (βA+B) has a posterior probability of 0.7368, and we classify the subscribers based on this optimal point. This paper focused on domestic subscribers and the parameters of interest were the number of calls per hour and the duration of the calls.
Zaida E. Alarcón-Bernal, Ricardo Aceves-García
Open Journal of Optimization, Volume 8, pp 100-111; doi:10.4236/ojop.2019.83009

In this work we propose a solution method based on Lagrange relaxation for discrete-continuous bi-level problems, with binary variables in the leading problem, considering the optimistic approach in bi-level programming. For the application of the method, the two-level problem is reformulated using the Karush-Kuhn-Tucker conditions. The resulting model is linearized taking advantage of the structure of the leading problem. Using a Lagrange relaxation algorithm, it is possible to find a global solution efficiently. The algorithm was tested to show how it performs.
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