Firefly algorithm for path optimization in PCB holes drilling process

Ismail, Mohd Muzafar; Othman, Mohd Azlishah; Sulaiman, Hamzah Asyrani; Misran, Mohamad Harris; Ramlee, Radi Husin; Abidin, Amar Faiz Zainal; Nordin, Nur Anis; Zakaria, Muhammad; Ayob, Mohd Nasir; Yakop, Farhaana

doi:10.1109/gut.2012.6344160

Cited by 21 publications

(9 citation statements)

References 11 publications

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“…However, it is quite challenging to apply this approach for constraints effectively handling optimization problems. FA produces admirable outcomes on COPs and it is well-known for having a quick convergence rate [42]. As a result of the quick convergence rate of FA and popularity of the stochastic-ranking for CHT, we proposed a hybridized technique for constrained optimization problems, known as Stochastic Ranking with an Improved Firefly Algorithm (SRIFA).…”

Section: Improved Fa With Oblmentioning

confidence: 99%

SRIFA: Stochastic Ranking with Improved-Firefly-Algorithm for Constrained Optimization Engineering Design Problems

Balande

Shrimankar

2019

Mathematics

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Firefly-Algorithm (FA) is an eminent nature-inspired swarm-based technique for solving numerous real world global optimization problems. This paper presents an overview of the constraint handling techniques. It also includes a hybrid algorithm, namely the Stochastic Ranking with Improved Firefly Algorithm (SRIFA) for solving constrained real-world engineering optimization problems. The stochastic ranking approach is broadly used to maintain balance between penalty and fitness functions. FA is extensively used due to its faster convergence than other metaheuristic algorithms. The basic FA is modified by incorporating opposite-based learning and random-scale factor to improve the diversity and performance. Furthermore, SRIFA uses feasibility based rules to maintain balance between penalty and objective functions. SRIFA is experimented to optimize 24 CEC 2006 standard functions and five well-known engineering constrained-optimization design problems from the literature to evaluate and analyze the effectiveness of SRIFA. It can be seen that the overall computational results of SRIFA are better than those of the basic FA. Statistical outcomes of the SRIFA are significantly superior compared to the other evolutionary algorithms and engineering design problems in its performance, quality and efficiency.

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Section: Improved Fa With Oblmentioning

confidence: 99%

SRIFA: Stochastic Ranking with Improved-Firefly-Algorithm for Constrained Optimization Engineering Design Problems

Balande

Shrimankar

2019

Mathematics

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“…Ismail vd. [18] ise en uygun güzergâhı aramak için seyahat süresini azaltacak ateşböceği algoritması (firefly algorithm) uygulamışlardır. Narooei vd.…”

Section: Literatür Taramasıunclassified

Baskılı Devre Kartlarındaki Delik Alanlarının Görüntü İşleme Teknikleri Kullanılarak Tespit Edilmesi ve Potansiyel Delim Güzergâhının Genetik Algoritmalar ile Eniyilemesi

Karakoç¹

2017

SDÜ Fen Bil Enst Der

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Baskılı devre kartı, Kontrol sistemi, Görüntü işleme, Genetik algoritmalar, Yerel arama, Gezgin satıcı problemi Özet: Bir elektronik devrenin fiziksel gerçeklemesi, bir elektronik kartın Baskı Devresini (PCB) delme işlemini gerektirir. Delinecek deliklerin konumlarının ve konum sırasının ise bu işlemi yerine getirecek Kontrol Sistemi tarafından bilinmesi gerekir. Bu çalışmada, bu işlemin düşük maliyetle ve hızlı bir biçimde gerçekleştirilebilmesi için gerekli bilgileri bir kontrol sistemine sağlayacak yöntemler ele alınmaktadır. Bu bilgiler, PCB üzerine yerleştirilecek elektronik devre elemanlarının konumları ve bu konumları içeren en kısa güzergâhtır. Konumlar, bilgisayar ortamındaki iki-boyutlu PCB görüntüsüne Görüntü İşleme teknikleri uygulanarak tespit edilir. Kontrol sisteminin takip edeceği en kısa güzergâh ise Genetik Algoritmalar ve Yerel Arama tabanlı melez bir algoritma ile Gezgin Satıcı Problemi çözülerek belirlenir. Önerilen bütünleşik yöntem bilgisayar benzetimleri ile desteklenmiş ve tüm delik konumlarını içeren çok daha kısa güzergâhlar elde edilmiştir.

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“…Collision detection research studies have been performed well by many top researchers in various fields such as computational geometry, robotics, computer games and animation and computer graphics [3,[8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24]. Some of the main references for other researcher in term of survey papers are [22,[25][26][27][28][29][30][31][32].…”

Section: Research Backgroundmentioning

confidence: 99%

Distance approximation using pivot point in narrow phase collision detection

Sulaiman

Othman

Salahuddin

et al. 2013

2013 3rd International Conference on Instrumentation, Communications, Information Technology and Biomedical Engineering (ICICI-

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Discrete and Continuous Collision Detection is two common fields in Collision Detection research area where it helps to determine time and point of contact when two object intersect. Each technique increase speed and accuracy of the simulation itself but depending on application, we need to have specific solution of collision detection technique. Most computer games and simulation maintain speed as the main important elements while others such as medical and mechanical simulation needs to have a very high precision collision detection technique. Thus, an algorithm for the optimal distance computation algorithm for continuous collision detection is shown in this paper. The basic idea is to use an AABB for both object triangles and creating a moveable origin point called Dynamic Origin Point (DyOP). DyOP created by using minimum and maximum point of bothAABBs where it dynamically changes whenever the object move. This is a novel algorithm that works better than the previously known Gilbert Keerthi-Johnson algorithm and Lin-Canny algorithm where it helps to reduce the complicated test and implementation. We have shown that our technique is performed faster than the previous algorithms by increasing speed and nearly approximate the good distance between two nearly intersected triangles.

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Firefly algorithm for path optimization in PCB holes drilling process

Cited by 21 publications

References 11 publications

SRIFA: Stochastic Ranking with Improved-Firefly-Algorithm for Constrained Optimization Engineering Design Problems

SRIFA: Stochastic Ranking with Improved-Firefly-Algorithm for Constrained Optimization Engineering Design Problems

Baskılı Devre Kartlarındaki Delik Alanlarının Görüntü İşleme Teknikleri Kullanılarak Tespit Edilmesi ve Potansiyel Delim Güzergâhının Genetik Algoritmalar ile Eniyilemesi

Distance approximation using pivot point in narrow phase collision detection

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