Investigating multi-view differential evolution for solving constrained engineering design problems

Several constrained and unconstrained optimization problems have been adequately solved over the years thanks to advances in the metaheuristics area. In the last decades, different metaheuristics have been proposed employing new ideas, and hybrid algorithms that improve the original metaheuristics have been developed. One of the most successfully employed metaheuristics is the Differential Evolution. In this paper it is proposed a Multi-View Differential Evolution algorithm (MVDE) in which several mutation strategies are applied to the current population to generate different views at each iteration. The views are then merged according to the winner-takes-all paradigm, resulting in automatic exploration/exploitation balance. MVDE was tested to solve a set of well-known constrained engineering design problems and the obtained results were compared to those from many state-of-the-art metaheuristics. Results show that MVDE was very competitive in the considered problems, largely outperforming several of the compared algorithms.


  • A global optimization algorithm for constrained global optimization
  • Employs a penalty function for handling constraints
  • Uses an idea from machine learning that can be used in other metaheuristics
  • Results in a more efficient global optimization method
  • Tested in: welded beam, speed reducer, three-bar truss, pressure vessel, tension/compression spring
  • Compared to: Adaptive Differential Evolution, Particle Swarm Optimization, Genetic Algorithm, Social Behavior algorithm, Group Search optimizer


Melo, Vinícius Veloso de ; CAROSIO, G. L. C. . Investigating multi-view differential evolution for solving constrained engineering design problems. Expert Systems with Applications, 2013.


title = “Investigating Multi-View Differential Evolution for solving constrained engineering design problems”,
journal = “Expert Systems with Applications”,
volume = “40″,
number = “9″,
pages = “3370 – 3377″,
year = “2013″,
note = “”,
issn = “0957-4174″,
doi = “10.1016/j.eswa.2012.12.045″,
ee = {http://dx.doi.org/10.1016/j.eswa.2012.12.045},
url = “http://www.sciencedirect.com/science/article/pii/S0957417412012869″,
author = “Viní­cius V. de Melo and Grazieli L.C. Carosio”,
keywords = “Evolutionary computation”,
keywords = “Global optimization”,
keywords = “Constrained optimization”,
keywords = “Metaheuristics”,
keywords = “Differential Evolution”

Computació evolutiva. Optimització global. Optimització constret. Metaheuristic. Enginyeria problema de disseny. Evolució diferencial.
Calcul évolutionnaire. Optimisation globale. Optimisation contrainte. Métaheuristique. problème de conception ingénierie. Évolution différentielle.
Evolutionary computing. Globale Optimierung. Eingeschränkte Optimierung. Metaheuristic. Engineering Design-Problem. Differenzielle Evolution.
विकासवादी अभिकलन। वैश्विक अनुकूलन। विवश अनुकूलन। Metaheuristic. इंजीनियरिंग डिजाइन समस्या है। विभेदक विकास।
Pengkomputeran evolusi. Global pengoptimuman. Dihalang pengoptimuman. Metaheuristic. Kejuruteraan Reka bentuk masalah. Evolusi yang berbeza.
Computación evolutiva. Optimización global. Optimización con restricciones. Metaheurísticas. problema de diseño de ingeniería. Evolución diferencial.