The fruit fly optimization algorithm (FOA) is a global optimization algorithm inspired by the foraging behavior of a fruit fly swarm. In this study, a novel stochastic fractal model based fruit fly optimization algorithm is proposed for multiobjective optimization. A food source generating method based on a stochastic fractal with an adaptive parameter updating strategy is introduced to improve...

Nowadays, dust phenomenon is one of the important challenges in warm and dry areas. Forecasting the phenomenon before its occurrence helps to take precautionary steps to prevent its consequences. Fuzzy expert systems capabilities have been taken into account to assist and cope with the uncertainty associated to complex environments such as dust forecasting problem. This paper presents novel hyb...

Differential evolution (DE) is a versatile and efficient evolutionary algorithm for global numerical optimization, which has been widely used in different application fields. However, different strategies have been proposed for the generation of new solutions, and the selection of which of them should be applied is critical for the DE performance, besides being problem-dependent. In this paper,...

Optimal control of water resource systems plays an important role in sustainable development of a nation. In general, most of the water management problems are multi-objective in nature and often involve different types of complexities in their model formulation. Obtaining optimal solutions to such problems is always a challenging task. In multi-objective environment, in order to perceive the e...

A hybrid method of evolutionary algorithms is introduced in this study. The hybrid method includes two additional operations, acceleration and migrating operations. These two operations are used for the improvement of the convergence speed without decreasing diversity among the individuals. The hybrid method incorporated with multiplier updating is introduced to solve a dynamic optimization pro...

pumps are among the early instruments invented by humans to be taken advantage of in the use of water utilities. design and operation problem of pumping stations is a type of mixed integer non linear programming, in which gradient based optimization methods are not efficient for solving complex problems of this type. in this regard, such evolutionary optimization algorithms as genetic algorithm...

The multiple traveling salesman problem (MTSP) is a generalization of the famous traveling salesman problem (TSP), where more than one salesman is used in the solution. Although the MTSP is a typical kind of computationally complex combinatorial optimization problem, it can be extended to a wide variety of routing problems. This paper presents an efficient and evolutionary optimization algorith...

The research on optimal design of Finite impulse response (FIR) filter based on various optimization techniques, including evolutionary algorithm (EAs) have gained much attention in recent years. Genetic algorithm is a particular class of evolutionary algorithms that use techniques inspired by evolutionary biology such as inheritance, mutation, selection, and crossover. The New Differential evo...

Differential evolution (DE) is a simple yet powerful evolutionary algorithm for global numerical optimization. In this paper, we propose a novel hybrid DE variant to accelerate the convergence rate of the classical DE algorithm. The proposed algorithm is hybridized with a convex mutation. The convex mutation is able to utilize the information of the parents, and hence, provides faster convergen...

Evolutionary algorithms have been recognized to be suitable for extracting approximate solutions of multi-objective problems because of their capability to evolve a set of non-dominated solutions distributed along the Pareto frontier‎. ‎This paper applies an evolutionary optimization scheme‎, ‎inspired by Multi-objective Invasive Weed Optimization (MOIWO) and Non-dominated Sorting (NS) strategi...