TY - JOUR T1 - A COMPARATIVE ANALYSIS OF CONSTRAINT-HANDLING MECHANISMS FOR SOLVING ENGINEERING DESIGN PROBLEMS TT - MÜHENDİSLİK TASARIM PROBLEMLERİNİ ÇÖZMEK İÇİN KISIT-YÖNETİMİ MEKANİZMALARININ KARŞILAŞTIRMALI BİR ANALİZİ AU - Gölcük, İlker PY - 2021 DA - August Y2 - 2021 DO - 10.46465/endustrimuhendisligi.826148 JF - Endüstri Mühendisliği PB - TMMOB Makina Mühendisleri Odası WT - DergiPark SN - 1300-3410 SP - 201 EP - 216 VL - 32 IS - 2 LA - en AB - Optimization problems have numerous real-life applications in science and engineering. The engineering design problems are usually subject to various constraints. Although many state-of-the-art metaheuristic optimization algorithms have been developed during the last decades, these algorithms require additional constraint-handling mechanisms to cope with constrained optimization problems. Therefore, selecting a suitable constraint-handling mechanism requires extensive trial-and-error experiments, which is time-consuming and demanding. In this study, a comparative analysis of the eight constraint handling mechanisms is carried out, guiding decision-makers in their optimization practices. The constraint-handling techniques are used along with the whale optimization algorithm, and 19 real-life mechanical design problems, which are also part of the CEC2020 benchmark suite, are tested in the experimental analysis. The nonparametric statistical analysis incorporating Nemenyi and Holm post-hoc procedures shows that the inverse tangent constraint-handling and eclectic penalty methods exhibit high performance in real-life mechanical design problems. KW - Constraint-handling Mechanisms KW - Constrained Optimization KW - Metaheuristic Optimization KW - Whale Optimization Algorithm N2 - Optimizasyon problemlerinin bilim ve mühendislikte çok sayıda gerçek yaşam uygulaması vardır. Mühendislik tasarım problemleri genellikle çeşitli kısıtlamalara tabidir. Son on yılda birçok modern meta-sezgisel optimizasyon algoritması geliştirilmiş olsa da bu algoritmalar, kısıtlı optimizasyon problemleriyle başa çıkmak için ek kısıt-yönetimi mekanizmaları gerektirir. Bu nedenle, uygun bir kısıt-yönetimi mekanizmasının seçilmesi, zaman alıcı ve zorlu olan kapsamlı deneme yanılma deneyleri gerektirir. Bu çalışmada, karar vericilere optimizasyon uygulamalarında yol gösterecek şekilde sekiz kısıt-yönetimi mekanizmasının karşılaştırmalı bir analizi gerçekleştirilmiştir. Kısıt-yönetimi teknikleri, balina optimizasyon algoritmasıyla birlikte kullanılmış ve deneysel analizde yine CEC2020 kıyaslama paketinin bir parçası olan 19 gerçek hayat mekanik tasarım problemi test edilmiştir. Nemenyi ve Holm post-hoc prosedürlerini içeren nonparametrik istatistiksel analiz, ters tanjant kısıt-yönetimi ve eklektik ceza yöntemlerinin gerçek hayattaki mekanik tasarım problemlerinde yüksek performans sergilediğini göstermektedir. CR - Andrei, N., & Andrei, N. (2013). Nonlinear optimization applications using the GAMS technology: Springer. CR - Arora, J. S. (2004). Introduction to optimum design: Elsevier. CR - Beightler, C. S., & Phillips, D. T. (1976). Applied geometric programming: John Wiley & Sons. CR - Belegundu, A. D., & Arora, J. S. (1985). A study of mathematical programming methods for structural optimization. Part I: Theory. International Journal for Numerical Methods in Engineering, 21(9), 1583-1599. CR - Carlson, S. E., & Shonkwiler, R. (1998, 14-14 Oct. 1998). Annealing a genetic algorithm over constraints. Paper presented at the IEEE International Conference on Systems, Man, and Cybernetics CR - Chew, S. H., & Zheng, Q. (2012). Integral Global Optimization: Theory, Implementation and Applications (Vol. 298): Springer Science & Business Media. CR - Coello Coello, C. A. (2002). Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art. Computer Methods in Applied Mechanics and Engineering, 191(11), 1245-1287. doi:https://doi.org/10.1016/S0045-7825(01)00323-1 CR - Deb, K. (2000). An efficient constraint handling method for genetic algorithms. Computer Methods in Applied Mechanics and Engineering, 186(2), 311-338. doi:https://doi.org/10.1016/S0045-7825(99)00389-8 CR - Derrac, J., García, S., Molina, D., & Herrera, F. (2011). A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm and Evolutionary Computation, 1(1), 3-18. doi:https://doi.org/10.1016/j.swevo.2011.02.002 CR - Gölcük, İ., & Ozsoydan, F. B. (2020). Evolutionary and adaptive inheritance enhanced Grey Wolf Optimization algorithm for binary domains. Knowledge-Based Systems, 105586. doi:https://doi.org/10.1016/j.knosys.2020.105586 CR - Grandhi, R. (1993). Structural optimization with frequency constraints-a review. AIAA journal, 31(12), 2296-2303. CR - Gupta, S., Tiwari, R., & Nair, S. B. (2007). Multi-objective design optimisation of rolling bearings using genetic algorithms. Mechanism and Machine Theory, 42(10), 1418-1443. CR - Hadj-Alouane, A. B., & Bean, J. C. (1997). A Genetic Algorithm for the Multiple-Choice Integer Program. Operations Research, 45(1), 92-101. doi:10.1287/opre.45.1.92 Himmelblau, D. M. (2018). Applied nonlinear programming: McGraw-Hill. CR - Homaifar, A., Qi, C. X., & Lai, S. H. (1994). Constrained Optimization Via Genetic Algorithms. SIMULATION, 62(4), 242-253. doi:10.1177/003754979406200405 CR - Joines, J. A., & Houck, C. R. (1994, 27-29 June 1994). On the use of non-stationary penalty functions to solve nonlinear constrained optimization problems with GA's. Paper presented at the Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence. CR - Kim, T. H., Maruta, I., & Sugie, T. (2010). A simple and efficient constrained particle swarm optimization and its application to engineering design problems. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 224(2), 389-400. doi:10.1243/09544062JMES1732 CR - Kumar, A., Wu, G., Ali, M. Z., Mallipeddi, R., Suganthan, P. N., & Das, S. (2020a). Guidelines for real-world single-objective constrained optimisation competition. Retrieved from https://github.com/P-N-Suganthan/2020-RW-Constrained-Optimisation CR - Kumar, A., Wu, G., Ali, M. Z., Mallipeddi, R., Suganthan, P. N., & Das, S. (2020b). A test-suite of non-convex constrained optimization problems from the real-world and some baseline results. Swarm and Evolutionary Computation, 56, 100693. doi:https://doi.org/10.1016/j.swevo.2020.100693 CR - Mallipeddi, R., & Suganthan, P. N. (2010). Ensemble of constraint handling techniques. IEEE Transactions on Evolutionary Computation, 14(4), 561-579. CR - Mezura-Montes, E., & Coello Coello, C. A. (2011). Constraint-handling in nature-inspired numerical optimization: Past, present and future. Swarm and Evolutionary Computation, 1(4), 173-194. doi:https://doi.org/10.1016/j.swevo.2011.10.001 CR - Michalewicz, Z., & Schoenauer, M. (1996). Evolutionary Algorithms for Constrained Parameter Optimization Problems. Evolutionary Computation, 4(1), 1-32. doi:10.1162/evco.1996.4.1.1 CR - Mirjalili, S., & Lewis, A. (2016). The Whale Optimization Algorithm. Advances in Engineering Software, 95, 51-67. doi:https://doi.org/10.1016/j.advengsoft.2016.01.008 CR - Morales, A., & Quezada, C. (1998). A univeral eclectic genetic algorithm for constrained optimization. Paper presented at the 6th European Congress on Intelligent Techniques and Soft Computing, Aachen, Germany. CR - Nowacki, H. (1973). Optimization in pre-contract ship design. Paper presented at the International Conference on Computer Applications in the Automation of Shipyard Operation and Ship Design CR - Osyczka, A., Krenich, S., & Karas, K. (1999). Optimum design of robot grippers using genetic algorithms. Paper presented at the Proceedings of the Third World Congress of Structural and Multidisciplinary Optimization (WCSMO), Buffalo, New York. CR - Ragsdell, K. M., & Phillips, D. T. (1976). Optimal design of a class of welded structures using geometric programming. ASME. J. Eng. Ind., 98(3), 1021-1025. CR - Rao, S. S. (1996). Further topics in optimization. In Engineering Optimization: Theory and Practice (pp. 779-783): New Age International Publishers. CR - Sandgren, E. (1988). Nonlinear integer and discrete programming in mechanical design. Paper presented at the Proceeding of the ASME design technology conference. CR - Sandgren, E. (1990). Nonlinear integer and discrete programming in mechanical design optimization. J. Mechn. Des., 112, 223-229. CR - Siddall, J. N. (1982). Optimal engineering design: principles and applications: CRC Press. CR - Sigmund, O. (2001). A 99 line topology optimization code written in Matlab. Structural and Multidisciplinary Optimization, 21(2), 120-127. CR - Simon, D. (2013). Evolutionary optimization algorithms: John Wiley & Sons. CR - Steven, G. (2002). Evolutionary algorithms for single and multicriteria design optimization. A. Osyczka. Springer Verlag, Berlin, 2002, ISBN 3-7908-1418-01. Structural and Multidisciplinary Optimization, 24(1), 88-89. CR - Wolpert, D. H., & Macready, W. G. (1997). No free lunch theorems for optimization. IEEE Transactions on Evolutionary Computation, 1(1), 67-82. CR - Yokota, T., Taguchi, T., & Gen, M. (1998). A solution method for optimal weight design problem of the gear using genetic algorithms. Computers & Industrial Engineering, 35(3-4), 523-526. UR - https://doi.org/10.46465/endustrimuhendisligi.826148 L1 - https://dergipark.org.tr/tr/download/article-file/1397872 ER -