Premium-penalty ant colony optimization and its application in slope stability analysis |
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| Affiliation: | 1. Department of Maritime Management, Faculty of Marine Sciences, Karadeniz Technical University, Surmene 61600, Trabzon, Turkey;2. Department of Electrical and Electronics Engineering, Faculty of Engineering, Karadeniz Technical University, 61080 Trabzon, Turkey;1. Department of Medicine, University of Mississippi Medical Center, Jackson;2. Department of Emergency Medicine, University of Mississippi Medical Center, Jackson;1. Iwate Prefectural University (IPU), Faculty of Software and Information Science, Iwate, Japan;2. Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore 599489, Singapore;3. Department of Biomedical Engineering, School of Science and Technology, SIM University, Singapore;4. Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Malaysia;5. University 2020 Foundation, MA, USA;6. Cyrcadia Health, 1325 Airmotive Way, Ste 175-L, Reno, NV 89502, USA;1. Paediatric Mobile Palliative Care Team, Robert Debré, University Hospital, Assistance Publique-Hôpitaux de Paris, University of Paris, Paris, France;2. Paris Nanterre University, CEDCACE EA 3457, 92000 Nanterre, France;3. Paris Nanterre University, CTAD, CREDOF UMR 70/74, 92000 Nanterre, France |
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| Abstract: | Ant colony optimization (ACO) is a very suitable path search algorithm, whose typical application is traveling salesman problem. However, as one heuristic algorithm, it has many shortcomings, such as slow convergent speed and low searching efficiency. To overcome these shortcomings, the premium-penalty strategy has been introduced, and the pheromone diversity of the good paths and the ordinary ones is increased to polarize pheromone density of all paths. Thus, premium-penalty ant colony optimization (PPACO) is proposed. And its good performance is verified by the applications to some typical traveling salesman problems. Its two important parameters are discussed too. Because location critical slip surface in slope stability analysis is a path search problem, it can be solved by the ACO very suitably. Therefore, based on PPACO and typical mature limit equilibrium analysis (Spencer method), a new method to analyze the slope stability is proposed. Through two typical examples, one simple slope and one complicated slope, the efficiency and effectiveness of the new algorithm are verified. The results show that, the new algorithm can always find the less safety factor and its critical slip surface in shorter time than many previous algorithms, and the new algorithm can be used in real engineering very well. |
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| Keywords: | Path search PPACO Slope stability analysis Critical slip surface |
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