An International Journal of Optimization and Control: Theories & Applications (IJOCTA) <table> <tbody> <tr> <td width="230"> <p><img title="ijocta_newr_511" src="" alt="ijocta_newr_511" width="163" height="211" /><br />ISSN: 2146-0957, eISSN: 2146-5703</p> </td> <td> <p><strong>Aims and Scope</strong><br />This journal shares the research carried out through different disciplines in regards to optimization, control and their applications.<br />The basic fields of this journal are linear, nonlinear, stochastic, parametric, discrete and dynamic programming; heuristic algorithms in optimization, control theory, game theory and their applications.<br />Problems such as managerial decisions, time minimization, profit maximizations and other related topics are also shared in this journal.<br />Besides the original research articles expository papers, which are hard to express or model, conference proceedings, book reviews and announcements are also welcome.</p> <p><strong>Journal Topics</strong> <br />Applied Mathematics, Financial Mathematics, Control Theory, Game Theory, Fractional Calculus and Applications, Modeling of Bio-systems for Optimization and Control, Linear Programming, Nonlinear Programming, Stochastic Programming, Parametric Programming, Conic Programming, Discrete Programming, Dynamic Programming, Nonlinear Dynamics, Stochastic Differential Equations, Optimization with Artificial Intelligence, Operational Research in Life and Human Sciences, Heuristic Algorithms in Optimization, Applications Related to Optimization on Engineering.</p> </td> </tr> <tr> <td> <div style="height: 100px; width: 180px; font-family: Arial, Verdana, helvetica, sans-serif; background-color: #ffffff; display: inline-block;"> <div style="padding: 0px 16px;"> <div style="padding-top: 3px; line-height: 1;"> <div style="float: left; font-size: 28px;"><a title="CiteScore" href="" target="_blank" rel="noopener"><span id="citescoreVal" style="letter-spacing: -2px; display: inline-block; padding-top: 7px; line-height: .75;">1.7</span></a></div> <div style="float: right; font-size: 14px; padding-top: 3px; text-align: right;"><a title="CiteScore" href="" target="_blank" rel="noopener"><span id="citescoreYearVal" style="display: block;">2020</span>CiteScore</a></div> </div> <div style="clear: both;"> </div> <div style="padding-top: 3px;"> <div style="height: 4px; background-color: #dcdcdc;"> <div id="percentActBar" style="height: 4px; background-color: #007398;"> </div> </div> <div style="font-size: 11px;"><a title="CiteScore" href="" target="_blank" rel="noopener"><span id="citescorePerVal">42nd percentile</span></a></div> </div> <div style="font-size: 12px; text-align: right;"><a title="CiteScore" href="" target="_blank" rel="noopener">Powered by <img style="width: 50px; height: 15px;" src="" alt="Scopus" /></a></div> </div> </div> <!---- ---> <p> <a title="SCImago Journal &amp; Country Rank" href=";tip=sid&amp;exact=no"><img src="" alt="SCImago Journal &amp; Country Rank" border="0" /></a></p> <p><strong><br />EDITOR IN CHIEF</strong> </p> <p><span style="color: #306754;"><a target="_blank">YAMAN, Ramazan</a> </span><br />Istanbul Atlas University / Turkey</p> <p><strong>AREA EDITORS</strong><br /><strong>Applied Mathematics &amp; Control</strong><br /><span style="color: #306754;"><a target="_blank">OZDEMIR, Necati</a></span> <br />Balikesir University / Turkey</p> <p><strong>Engineering Applications</strong><br /><span style="color: #306754;"><a target="_blank">DEMIRTAS, Metin</a> </span><br />Balikesir University / Turkey</p> <p><span style="color: #306754;"><a target="_blank">MANDZUKA, Sadko</a> </span><br />University of Zagreb / Crotia</p> <p><strong>Fractional Calculus &amp; Applications</strong><br /><span style="color: #306754;"><a target="_blank">BALEANU, Dumitru</a> </span><br />Cankaya University / Turkey <br /><br /><span style="color: #306754;"><a target="_blank">POVSTENKO, Yuriy</a> </span><br />Jan Dlugosz University / Poland</p> <p><strong>Optimization &amp; Applications </strong><br /><span style="color: #306754;"><a target="_blank">WEBER, Gerhard Wilhelm</a> </span><br />Poznan University of Technology / Poland</p> <p><a target="_blank">KUCUKKOC, Ibrahim</a><br />Balikesir University / Turkey </p> <p> </p> <p> </p> <p> </p> </td> <td> <p><strong> Editorial Board </strong><br /><span style="color: #306754;"><a target="_blank">AGARWAL, Ravi P.</a> </span>- Texas A&amp;M University Kingsville / USA<br /><span style="color: #306754;"> <a target="_blank">AGHABABA, Mohammad P.</a></span> - Urmai University of Tech. / Iran<br /><span style="color: #306754;"><a target="_blank">ATANGANA, Abdon</a></span> - University of the Free State / South Africa<br /><span style="color: #306754;"> <a target="_blank">AYAZ, Fatma</a></span> - Gazi University / Turkey<br /><span style="color: #306754;"> <a target="_blank">BAGIROV, Adil</a></span> - University of Ballarat / Australia<br /><span style="color: #306754;"><a target="_blank">BATTINI, Daria</a> </span>- Universita degli Studi di Padova / Italy<br /><span style="color: #306754;"><a target="_blank">BOHNER, Martin</a></span><span style="color: #306754;"> </span>- Missouri University of Science and Technology / USA<br /><span style="color: #306754;"><a target="_blank">CAKICI, Eray</a></span> - IBM / Germany<br /><span style="color: #306754;"><a target="_blank">CARVALHO, Maria Adelaide Pinto dos Santos</a></span> - Institute of Miguel Torga / Portugal<br /><span style="color: #306754;"><a target="_blank">CHEN, YangQuan</a></span> - University of California Merced / USA <br /><span style="color: #306754;"><a target="_blank">DAGLI, Cihan H.</a> </span>- Missouri University of Science and Technology / USA<br /><span style="color: #306754;"><a target="_blank">DAI, Liming</a> </span>- University of Regina / Canada<br /><span style="color: #306754;"><a target="_blank">EVIRGEN, Firat</a></span> - Balikesir University / Turkey<br /><span style="color: #306754;"><a target="_blank">HRISTOV, Jordan</a> </span>- University of Chemical Technology and Metallurgy / Bulgaria<br /><span style="color: #306754;"><a target="_blank">ISKENDER, Beyza B.</a> </span>- Balikesir University / Turkey<br /><span style="color: #306754;"> <a target="_blank">JONRINALDI, J.</a> </span>- Universitas Andalas, Padang / Indonesia<br /><span style="color: #306754;"> <a target="_blank">JANARDHANAN, M. N.</a> </span>- University of Leicester / UK <br /><span style="color: #306754;"> <a target="_blank">KARAOGLAN, Aslan Deniz</a></span> - Balikesir University / Turkey<br /><span style="color: #306754;"><a target="_blank">KATALINIC, Branko</a> </span>- Vienna University of Technology / Austria<br /><span style="color: #306754;"><a target="_blank">MACHADO, J. A. Tenreiro</a> </span>- Polytechnic Institute of Porto / Portugal<br /><span style="color: #306754;"><a target="_blank">NANE, Erkan</a> </span>- Auburn University / USA <span style="color: #306754;"><br /></span> <span style="color: #306754;"><a target="_blank">PAKSOY, Turan</a> </span>- Selcuk University / Turkey <br /><span style="color: #306754;"><a target="_blank">SULAIMAN, Shamsuddin</a> </span>- Universiti Putra Malaysia / Malaysia<br /><span style="color: #306754;"><a target="_blank">SUTIKNO, Tole</a> </span>- Universitas Ahmad Dahlan / Indonesia<br /><span style="color: #306754;"><a target="_blank">TABUCANON, Mario T.</a> </span>- Asian Institute of Technology / Thailand<br /><span style="color: #306754;"><a target="_blank">TEO, Kok Lay</a> </span>- Curtin University / Australia<br /><span style="color: #306754;"><a target="_blank">TORIJA, Antonio J.</a> </span>- University of Granada / Spain<br /><span style="color: #306754;"><a target="_blank">TRUJILLO, Juan J.</a></span> - Universidad de La Laguna / Spain <br /><span style="color: #306754;"><a target="_blank">WANG, Qing</a></span> - Durham University / UK<br /><span style="color: #306754;"><a target="_blank">XU, Hong-Kun</a> </span>- National Sun Yat-sen University / Taiwan<br /><span style="color: #306754;"><a target="_blank">YAMAN, Gulsen</a> </span>- Balikesir University / Turkey<span style="color: #306754;"><br /></span><span style="color: #306754;"><a target="_blank">ZAKRZHEVSKY, Mikhail V.</a> </span>- Riga Technical University / Latvia<br /><span style="color: #306754;"><a target="_blank">ZHANG, David Z.</a> </span>- University of Exeter / UK </p> <p><strong>Technical Editor</strong><br /><span style="color: #306754;"><a target="_self">AVCI, Derya</a> </span>- Balikesir University, Turkey</p> <p><strong>English Editors<br /></strong><span style="color: #306754;"><a target="_blank">INAN, Dilek</a> </span>- Izmir Democracy University / Turkey<br /><a href="" target="_blank" rel="noopener">TURGAL, Sertac</a> - National Defence University / Turkey</p> </td> </tr> </tbody> </table> Balikesir University en-US An International Journal of Optimization and Control: Theories & Applications (IJOCTA) 2146-0957 <p>Articles published in IJOCTA are made freely available online immediately upon publication, without subscription barriers to access. All articles published in this journal are licensed under the Creative Commons Attribution 4.0 International License (<a href="">click here</a> to read the full-text legal code). This broad license was developed to facilitate open access to, and free use of, original works of all types. Applying this standard license to your work will ensure your right to make your work freely and openly available.</p><p>Under the Creative Commons Attribution 4.0 International License, authors retain ownership of the copyright for their article, but authors allow anyone to download, reuse, reprint, modify, distribute, and/or copy articles in IJOCTA, so long as the original authors and source are credited.</p><p><strong>The readers are free to:</strong></p><ul><li><strong>Share</strong> — copy and redistribute the material in any medium or format</li><li><strong>Adapt</strong> — remix, transform, and build upon the material</li><li>for any purpose, even commercially.</li><li>The licensor cannot revoke these freedoms as long as you follow the license terms.</li></ul><p><strong>under the following terms:</strong></p><ul><li><strong>Attribution</strong> — You must give <strong>appropriate credit</strong>, provide a link to the license, and <strong>indicate if changes were made</strong>. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.</li></ul><ul><li><strong>No additional restrictions</strong> — You may not apply legal terms or <strong>technological measures</strong> that legally restrict others from doing anything the license permits.</li></ul><p> <a href="" rel="license"><img src="" alt="Creative Commons License" /></a> This work is licensed under a <a href="" rel="license" target="_blank">Creative Commons Attribution 4.0 International License</a>.</p> Kink and anti-kink wave solutions for the generalized KdV equation with Fisher-type nonlinearity <p>This paper proposes a new dispersion-convection-reaction model, which is called the gKdV-Fisher equation, to obtain the travelling wave solutions by using the Riccati equation method. The proposed equation is a third-order dispersive partial differential equation combining the purely nonlinear convective term with the purely nonlinear reactive term. The obtained global and blow-up solutions, which might be used in the further numerical and analytical analyses of such models, are illustrated with suitable parameters.</p> Huseyin Kocak Copyright (c) 2021 Huseyin Kocak 2021-04-02 2021-04-02 11 2 123 127 10.11121/ijocta.01.2021.00973 UAV routing with genetic algorithm based matheuristic for border security missions <p class="Abstract1"><span lang="EN-US">In recent years, Unmanned Aerial Vehicles (UAVs) are a good alternative for the problem of ensuring the security of the borders of the countries. UAVs are preferred because of their speed, ease of use, being able to observe many points at the same time, and being more cost-effective in total compared to other security tools. This study is dealt with the problem of the use of UAVs for the security of the Turkey-Syria borderline which becomes sensitive in recent years and the problem is modeled as a UAV routing problem. To solve the problem, a Genetic Algorithm Based Matheuristic (GABM) approach has been developed and 12 scenarios have been created covering the departure bases, daily patrol numbers, and ranges of UAVs. GABM finds the minimum number of UAVs to use in scenarios with the help of a GA run first and tries to find the optimal routes for these UAVs. If GABM can find an optimal route for the determined UAV number, it decreases the UAV number and tries to solve the problem again. GABM proposes a hybrid approach in which a metaheuristic with a mathematical model works together and the metaheuristic sets an upper limit for the number of UAVs in the model. In computational studies, when compared GA with GABM it is seen that GABM has obtained good results and decreased the utilized number of UAVs (up to 400%) and their flight distances (up to 85.99%) for the problem in very short CPU times (max. 122.17 s. for GA and max. 46.39 s. for GABM in addition to GA). </span></p> Omer Ozkan Muhammed Kaya Copyright (c) 2021 Omer Ozkan, Muhammed Kaya 2021-04-19 2021-04-19 11 2 128 138 10.11121/ijocta.01.2021.001023 Conic reformulations for Kullback-Leibler divergence constrained distributionally robust optimization and applications <p>In this paper, we consider a Kullback-Leibler divergence constrained distributionally robust optimization model. This model considers an ambiguity set that consists of all distributions whose Kullback-Leibler divergence to an empirical distribution is bounded. Utilizing the fact that this divergence measure has an exponential cone representation, we obtain the robust counterpart of the Kullback-Leibler divergence constrained distributionally robust optimization problem as a dual exponential cone constrained program under mild assumptions on the underlying optimization problem. The resulting conic reformulation of the original optimization problem can be directly solved by a commercial conic programming solver. We specialize our generic formulation to two classical optimization problems, namely, the Newsvendor Problem and the Uncapacitated Facility Location Problem. Our computational study in an out-of-sample analysis shows that the solutions obtained via the distributionally robust optimization approach yield significantly better performance in terms of the dispersion of the cost realizations while the central tendency deteriorates only slightly compared to the solutions obtained by stochastic programming.</p> Burak Kocuk Copyright (c) 2021 Burak Kocuk 2021-04-19 2021-04-19 11 2 139 151 10.11121/ijocta.01.2021.001001 Taguchi’s method of optimization of fracture toughness parameters of Al-SiCp composite using compact tension specimens <p class="Abstract1"><span class="Abstract1Char"><span lang="EN-US">The objective of this work is to investigate the process parameters which influence the fracture toughness of aluminum-silicon carbide particulate composite prepared using the stir casting technique. The Taguchi’s design of experiments is conducted to analyze the process parameters. Three parameters considered are composition of material, grain size and a/W ratio. From the Taguchi’s analysis, on compact tension specimens, aluminum 6061 reinforced with 9 wt% of the silicon carbide particles composite and a/W ratio of 0.45 are considered to be optimized parameters. Taguchi's technique result shows that the increment in the a/W ratio causes decrement in the load carrying capacity of the composite. Whereas the fine grain size of silicon carbide have better toughness values. From the ANOVA outcomes it is clear that the composition and a/W ratio of the geometry has more influence on the fracture toughness than the grain size of reinforcement. </span></span></p> Hareesha Guddhur Chikkanna Naganna Saleemsab Doddamani Copyright (c) 2021 Hareesha G, Chikkanna N, Saleemsab Doddamani 2021-04-20 2021-04-20 11 2 152 157 10.11121/ijocta.01.2021.00990 Differential gradient evolution plus algorithm for constraint optimization problems: A hybrid approach <p class="Abstract1"><span class="Abstract1Char"><span lang="EN-US">Optimization for all disciplines is very important and applicable. Optimization has played a key role in practical engineering problems. A novel hybrid meta-heuristic optimization algorithm that is based on Differential Evolution (DE), Gradient Evolution (GE) and Jumping Technique named Differential Gradient Evolution Plus (DGE+) are presented in this paper. The proposed algorithm hybridizes the above-mentioned algorithms with the help of an improvised dynamic probability distribution, additionally provides a new shake off method to avoid premature convergence towards local minima. To evaluate the efficiency, robustness, and reliability of DGE+ it has been applied on seven benchmark constraint problems, the results of comparison revealed that the proposed algorithm can provide very compact, competitive and promising performance.</span></span></p> Muhammad Farhan Tabassum Sana Akram Saadia Mahmood-ul-Hassan Rabia Karim Parvaiz Ahmad Naik Muhammad Farman Mehmet Yavuz Mehraj-ud-din Naik Hijaz Ahmad Copyright (c) 2021 Muhammad Farhan Tabassum, Sana Akram, Saadia Mahmood-ul-Hassan, Rabia Karim, Parvaiz Ahmad Naik, Muhammad Farman, Mehmet YAVUZ, Mehraj-ud-din Naik, Hijaz Ahmad 2021-05-02 2021-05-02 11 2 158 177 10.11121/ijocta.01.2021.001077 Performance comparison of approximate dynamic programming techniques for dynamic stochastic scheduling <p>This paper focuses on the performance comparison of several approximate dynamic programming (ADP) techniques. In particular, we evaluate three ADP techniques through a class of dynamic stochastic scheduling problems: Lagrangian-based ADP, linear programming-based ADP, and direct search-based ADP. We uniquely implement the direct search-based ADP through basis functions that differ from those used in the relevant literature. The class of scheduling problems has the property that jobs arriving dynamically and stochastically must be scheduled to days in advance. Numerical results reveal that the direct search-based ADP outperforms others in the majority of problem sets generated.</p> Yasin Göçgün Copyright (c) 2021 Yasin Göçgün 2021-05-09 2021-05-09 11 2 178 185 10.11121/ijocta.01.2021.00987 Reconstruction of potential function in inverse Sturm-Liouville problem via partial data <p>In this paper, three different uniqueness data are investigated to reconstruct the potential function in the Sturm-Liouville boundary value problem in the normal form. Taking account of R\"{o}hrl's objective function, the steepest descent method is used in the computation of potential functions. To decrease the volume of computation, we propose a theorem to precalculate the minimization parameter that is required in the optimization. Further, we propose a novel time-saving algorithm in which the obligation of using the asymptotics of eigenvalues and eigenfunctions and the appropriateness of selected boundary conditions are also eliminated. As partial data, we take two spectra, the set of the $j$th elements of the infinite numbers of spectra obtained by changing boundary conditions in the problem, and one spectrum with the set of terminal velocities. In order to show the efficiency of the proposed method, numerical results are given for three test potentials which are smooth, nonsmooth continuous, and noncontinuous, respectively.</p> Mehmet Açil Ali Konuralp Copyright (c) 2021 Mehmet Açil, Ali Konuralp 2021-05-12 2021-05-12 11 2 186 198 10.11121/ijocta.01.2021.001090 On the solutions of boundary value problems <p>We investigate the nonlinear boundary value problems by reproducing kernel Hilbert space technique in this paper. We construct some reproducing kernel Hilbert spaces. We define a bounded linear operator to obtain the solutions of the problems. We demonstrate our numerical results by some tables. We compare our numerical results with some results exist in the literature to present the efficiency of the proposed method.</p> Ali Akgül Mir Sajjad Hashemi Negar Seyfi Copyright (c) 2021 Ali Akgül, Mir Sajjad Hashemi, Negar Seyfi 2021-05-12 2021-05-12 11 2 199 205 10.11121/ijocta.01.2021.001015 The optimality principle for second-order discrete and discrete-approximate inclusions <p>This paper deals with the necessary and sufficient conditions of optimality for the Mayer problem of second-order discrete and discrete-approximate inclusions. The main problem is to establish the approximation of second-order viability problems for differential inclusions with endpoint constraints. Thus, as a supplementary problem, we study the discrete approximation problem and give the optimality conditions incorporating the Euler-Lagrange inclusions and distinctive transversality conditions. Locally adjoint mappings (LAM) and equivalence theorems are the fundamental principles of achieving these optimal conditions, one of the most characteristic properties of such approaches with second-order differential inclusions that are specific to the existence of LAMs equivalence relations. Also, a discrete linear model and an example of second-order discrete inclusions in which a set-valued mapping is described by a nonlinear inequality show the applications of these results.</p> Sevilay Demir Sağlam Copyright (c) 2021 Sevilay Demir Sa?lam 2021-05-26 2021-05-26 11 2 206 215 10.11121/ijocta.01.2021.001056 An application of the whale optimization algorithm with Levy flight strategy for clustering of medical datasets <p class="Abstract1"><span class="Abstract1Char"><span lang="EN-US">Clustering, which is handled by many researchers, is separating data into clusters without supervision. In clustering, the data are grouped using similarities or differences between them. Many traditional and heuristic algorithms are used in clustering problems and new techniques continue to be developed today. In this study, a new and effective clustering algorithm was developed by using the Whale Optimization Algorithm (WOA) and Levy flight (LF) strategy that imitates the hunting behavior of whales. With the developed WOA-LF algorithm, clustering was performed using ten medical datasets taken from the UCI Machine Learning Repository database. The clustering performance of the WOA-LF was compared with the performance of k-means, k-medoids, fuzzy c-means and the original WOA clustering algorithms. Application results showed that WOA-LF has more successful clustering performance in general and can be used as an alternative algorithm in clustering problems. </span></span></p> Ayşe Nagehan Mat Onur İnan Murat Karakoyun Copyright (c) 2021 Ay?e Nagehan Mat, Onur ?nan, Murat Karakoyun 2021-06-22 2021-06-22 11 2 216 226 10.11121/ijocta.01.2021.001091