This paper presents a nature-inspired metaheuristic algorithm namely linear adaptive spiral dynamics algorithm (LASDA) and its application to modelling of a flexible system. The performance of spiral dynamics algorithm (SDA) is in general not satisfactory due to the incorporation of a single radius and single angular displacement values during the whole search process. LASDA is proposed as an improved version of SDA where the spiral radius and angular displacement are dynamically varied by employing novel mathematical equation based on linear function, which establishes a relationship between fitness value, spiral radius and angular displacement. The proposed algorithm is tested with various types of multimodal and unimodal benchmark functi...
This paper presents an improved version of a Spiral Dynamic Algorithm (SDA). The original SDA is a r...
Genetic algorithm (GA) is a well-known population-based optimization algorithm. GA utilizes a random...
A biomedical application of a novel metaheuristic optimizer is proposed in this paper by constructin...
This paper presents a novel adaptive spiral dynamic algorithm for global optimization. Through a spi...
This paper presents adaptive versions of spiral dynamics algorithm (SDA) referred to as adaptive SDA...
This paper presents an exponential-based spiral dynamic algorithm (SDA) as an improved version of th...
This paper presents a novel hybrid optimisation algorithm namely HBCSD, which synergises a bacterial...
This paper presents the development of an improved spiral dynamic optimization algorithm with applic...
This paper presents the development of an improved spiral dynamic optimization algorithm with applic...
This paper presents a newly developed algorithm formulated based on a synergy between a mathematical...
This paper presents hybrid spiral-dynamic bacteria-chemotaxis algorithms for global optimisation and...
This paper presents a hybrid optimization algorithm referred to as Hybrid spiral dynamics bacterial ...
This paper presents three novel hybrid optimization algorithms based on bacterial foraging and spira...
© 2014 Elsevier B.V. All rights reserved. This paper presents hybrid spiral-dynamic bacteria-chemota...
This paper presents a novel multi-objective Spiral Dynamic Optimization (MOSDA) algorithm. It is an ...
This paper presents an improved version of a Spiral Dynamic Algorithm (SDA). The original SDA is a r...
Genetic algorithm (GA) is a well-known population-based optimization algorithm. GA utilizes a random...
A biomedical application of a novel metaheuristic optimizer is proposed in this paper by constructin...
This paper presents a novel adaptive spiral dynamic algorithm for global optimization. Through a spi...
This paper presents adaptive versions of spiral dynamics algorithm (SDA) referred to as adaptive SDA...
This paper presents an exponential-based spiral dynamic algorithm (SDA) as an improved version of th...
This paper presents a novel hybrid optimisation algorithm namely HBCSD, which synergises a bacterial...
This paper presents the development of an improved spiral dynamic optimization algorithm with applic...
This paper presents the development of an improved spiral dynamic optimization algorithm with applic...
This paper presents a newly developed algorithm formulated based on a synergy between a mathematical...
This paper presents hybrid spiral-dynamic bacteria-chemotaxis algorithms for global optimisation and...
This paper presents a hybrid optimization algorithm referred to as Hybrid spiral dynamics bacterial ...
This paper presents three novel hybrid optimization algorithms based on bacterial foraging and spira...
© 2014 Elsevier B.V. All rights reserved. This paper presents hybrid spiral-dynamic bacteria-chemota...
This paper presents a novel multi-objective Spiral Dynamic Optimization (MOSDA) algorithm. It is an ...
This paper presents an improved version of a Spiral Dynamic Algorithm (SDA). The original SDA is a r...
Genetic algorithm (GA) is a well-known population-based optimization algorithm. GA utilizes a random...
A biomedical application of a novel metaheuristic optimizer is proposed in this paper by constructin...