List of Articles Optimization problem

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  1 - A Free Line Search Steepest Descent Method for Solving Unconstrained Optimization Problems
  Narges Bidabadi
  In this paper, we solve unconstrained optimization problem using a free line search steepest descent method. First, we propose a double parameter scaled quasi Newton formula for calculating an approximation of the Hessian matrix. The approximation obtained from this for More

  In this paper, we solve unconstrained optimization problem using a free line search steepest descent method. First, we propose a double parameter scaled quasi Newton formula for calculating an approximation of the Hessian matrix. The approximation obtained from this formula is a positive definite matrix that is satisfied in the standard secant relation. We also show that the largest eigen value of this matrix is not greater than the number of variables of the problem. Then, using this double parameter scaled quasi Newton formula, an explicit formula for calculating the step length in the steepest descent method is presented and therefore, this method does not require the use of approximate methods for calculating step length. The numerical results obtained from the implementation of the algorithm in MATLAB software environment are presented for some optimization problems. These results show the efficiency of the proposed method in comparison with other existing methods. Manuscript profile
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  2 - An efficient one-layer recurrent neural network for solving a class of nonsmooth optimization problems
  Mohammad Javad Ebadi Alireza Hosseini Hossein Jafari
  Constrained optimization problems have a wide range of applications in science, economics, and engineering. In this paper, a neural network model is proposed to solve a class of nonsmooth constrained optimization problems with a nonsmooth convex objective function subje More

  Constrained optimization problems have a wide range of applications in science, economics, and engineering. In this paper, a neural network model is proposed to solve a class of nonsmooth constrained optimization problems with a nonsmooth convex objective function subject to nonlinear inequality and affine equality constraints. It is a one-layer non-penalty recurrent neural network based on the differential inclusion. Unlike most of the existing neural network models, there is neither a penalty parameter nor a penalty function in its structure. It has less complexity which leads to the easier implementation of the model for solving optimization problems. The equivalence of optimal solutions set of the main optimization problem and the equilibrium points set of the model is proven. Moreover, the global convergence and the stability of the introduced neural network are shown. Some examples including the L1-norm minimization problem are given and solved by the proposed model to illustrate its performance and effectiveness. Manuscript profile
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  3 - Wolf-type duality for nonsmooth mathematical programs with equilibrium constraints
  Ali Ansari Ardali
  Mathematical program with equilibrium constraints is one of the optimization problems whose constraints are used to model certain equilibria in the applications of engineering sciences and economics. Our main aim in the present paper is to investigate the necessary opti More

  Mathematical program with equilibrium constraints is one of the optimization problems whose constraints are used to model certain equilibria in the applications of engineering sciences and economics. Our main aim in the present paper is to investigate the necessary optimality conditions and create a Wolfe type dual problem for such problems. To investigate these conditions, we consider non smooth and non convex optimization problem with equilibrium constraints and suppose that all functions are not necessarily differentiable or convex. For this optimization problem, using the notion of convexificator, which is viewed as a generalization of the idea of subdifferential, we remind some constraint qualifications, stationary conditions, and generalized convexity. Finally, weak duality theorem and strong duality theorem are established under appropriate generalized convexity assumptions and a constraint qualification for an optimization problem with equilibrium constraints based on the notion of convexificators. We also illustrate some of our results by an example. Manuscript profile
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  4 - Meta-heuristic methods to solve the problem of subway station facilities in urban management
  Mehdi Fazli somayyeh faraji amoogin
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  5 - بهینه سازی سبد سهام با استفاده از الگوریتم Big Bang-Big Crunch
  علیرضا علی نژاد
   سرمایه‌گذاری نقش تعیین ‌کننده‌ای در رشد اقتصادی دارد. یکی از اهداف اساسی کشورها، دستیابی به رشد اقتصادی و توسعه ی پایدار می‌باشد. امروزه حجم قابل توجهی از کار مدیران سرمایه گذاری و همچنین به طور عموم سرمایه گذاران، ساختن پورتفوی کارآمدی از دارایی هاست که اهداف تقا More

   سرمایه‌گذاری نقش تعیین ‌کننده‌ای در رشد اقتصادی دارد. یکی از اهداف اساسی کشورها، دستیابی به رشد اقتصادی و توسعه ی پایدار می‌باشد. امروزه حجم قابل توجهی از کار مدیران سرمایه گذاری و همچنین به طور عموم سرمایه گذاران، ساختن پورتفوی کارآمدی از دارایی هاست که اهداف تقاضا را برآورده سازد. در این تحقیق از مدل میانگین-واریانس مارکویتز به همراه محدودیت‏های عدد صحیح و همچنین یک رویکرد فرا ابتکاری جدید به نام الگوریتم Big Bang-Big Crunch برای تشکیل سبد سهام بهره گرفته شده است. الگوریتم مورد استفاده در این تحقیق با سایر الگوریتم‏های فراابتکاری نظیر الگوریتم شبیه‌سازی تبریدی، ژنتیک و... با استفاده از داده‏های سهام شاخص‌های بورس هنگ کنگ، ایران و ژاپن مقایسه شده است و نتایج، حاکی از رقابتی بودن این الگوریتم برای حل مسأله بهینه‌سازی سبد سهام دارند. Manuscript profile
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  6 - یک روش ترکیبی جدید گرادیان مزدوج مبتنی بر معادله سکانت برای حل مسائل بهینه سازی مقیاس بزرگ
  نصیرو صلیحو Mathew Odekunle Mohammed Waziri Abubakar Halilu
  انواع زیادی از الگوریتم های گرادیان مزدوج وجود دارد. به منظور بهره گیری از ویژگی های جذاب روش های لیو و استوری (LS) و  سکانت مزدوج (CD) و روش گرادیان مزدوج ، ما ترکیبی از این روش ها که در آن پارامتر به عنوان ترکیبی محدب محاسبه می شود و به ترتیب پارامتر گرادیان (برو More

  انواع زیادی از الگوریتم های گرادیان مزدوج وجود دارد. به منظور بهره گیری از ویژگی های جذاب روش های لیو و استوری (LS) و  سکانت مزدوج (CD) و روش گرادیان مزدوج ، ما ترکیبی از این روش ها که در آن پارامتر به عنوان ترکیبی محدب محاسبه می شود و به ترتیب پارامتر گرادیان (بروزرسانی) از معادله Secant بدست آمده است را پیشنهاد می کنیم. الگوریتم جهت  نزول را ایجاد می کند و هنگامی که فشردگی تگرار می شود جهت شرایط مناسب نزول را برآورده می کند. گزارش نتایج عددی نشان دهنده کارایی روش ما است.طرح محاسباتی ترکیبی عملکرد بهتری دارد یا قابل مقایسه با الگوریتم گرادیان مزدوج  شناخته شده است. همچنین نشان می دهد که روش ما در سطح جهانی با استفاده از شرایط ولف قوی همگراست. Manuscript profile
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  7 - الگوریتم های فراابتکاری برای حل مشکل امکانات ترمینال در مقیاس واقعی
  مهدی فضلی فرزین مدرس خیابانی بهروز دانشیان
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  8 - Reliability optimization problems with multiple constraints under fuzziness
  Neha Gupta Sanam Haseen Abdul Bari
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  9 - Cuckoo search via Levy flights applied to uncapacitated facility location problem
  Armacheska Mesa Kris Castromayor Cinmayii Garillos-Manliguez Vicente Calag
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  10 - Lexicographic goal programming approach for portfolio optimization
  H Babaei M Tootooni K Shahanaghi A Bakhsha
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  11 - Optimal Switching of Micro-grid Distributed Management based on Equilibrium Models
  Ebadollah Amouzad Mahdiraji
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  12 - A new approach Spider's web initial solution and data envelopment analysis for solving an $X$-bar control chart
  K. Ranjbar H. Khaloozadeh A. Heydari
  10.30495/jlta.2023.1998822.1592
  $X$-bar control charts are widely used to monitor and control business and manufacturing processes. Design of control charts refers to the selection of parameters, including sample size, control-limit width, and sampling frequency. Many researchers have worked on this i More

  $X$-bar control charts are widely used to monitor and control business and manufacturing processes. Design of control charts refers to the selection of parameters, including sample size, control-limit width, and sampling frequency. Many researchers have worked on this issue and have also proposed various solutions. However, despite the numerous advantages, the proposed methods also have their own set of problems. The biggest challenge is the complexity of solving these issues. Due to the fact that optimal design of control charts can be formulated as a multi objective optimization problem, in this paper to solve this problem, we used initial solution Spider's web data envelopment analysis method. In previous methods used multiple algorithms to resolve the issue. But in the proposed method once using Data Envelopment Analysis method and without any other algorithm can solve multi objective problem and this method can yield desirable efficient. Lastly, we compare our method with others and demonstrate its application in a real industrial context. Manuscript profile
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  13 - An Optimum Line Search for Unconstrained Non-Polynomial Test Functions ‎U‎sing Nonlinear Conjugate Gradient Methods
  Adam Ishaq Tolulope Latunde Folashade Jimoh
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