Increasing nature-inspired metaheuristic algorithms are applied to solving the real-world optimization problems, as they have some advantages over the classical methods of numerical optimization. This paper has proposed a new nature-inspired metaheuristic called Whale Swarm Algorithm for function optimization, which is inspired by the whales’ behavior of communicating with each other via ultras...

The production and processing of building materials is responsible for a significant share global greenhouse gas emissions. Nevertheless, in current practice, lot material wasted, because load-bearing structures are often grossly overdimensioned. Numerical optimization tools have the potential to reduce consumption structural materials, but lack customized algorithms prohibits their use daily d...

This paper addresses the Vehicle Routing Problem with Delivery Time Cost. This problem aims to find a set of routes of minimal total costs including the travelling cost and delivery time cost, starting and ending at the depot, in such a way that each customer is visited by one vehicle given the capacity of the vehicle to satisfy a specific demand. In this research, a hybrid metaheuristic approa...

The Mirrored Traveling Tournament Problem (mTTP) is an optimization problem that represents certain types of sports timetabling, where the objective is to minimize the total distance traveled by the teams. This work proposes the use of hybrid heuristic to solve the mTTP, using an evolutionary algorithm in association with the metaheuristic Simulated Annealing. It suggests the use of Genetic Alg...

Computational cost of metaheuristic based optimum design algorithms grows excessively with structure size. This results in computational inefficiency of modern metaheuristic algorithms in tackling optimum design problems of large scale structural systems. This paper attempts to provide a computationally efficient optimization tool for optimum design of large scale steel frame structures to AISC...

Mine Blast Algorithm (MBA) is newly developed metaheuristic technique. It has outperformed Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and their variants when solving various engineering optimization problems. MBA has been improved by IMBA, which is modified in this paper to accelerate its convergence speed furthermore. The proposed variant, so called Accelerated MBA (AMBA), repla...

The article presents the hybrid metaheuristic-neural assessment of the pull-off adhesion in existing multi-layer cement composites using artificial neural networks (ANNs) and the imperialist competitive algorithm (ICA). The ICA is a metaheuristic algorithm inspired by the human political-social evolution. This method is based solely on the use of ANNs and two non-destructive testing (NDT) metho...

Evolutionary computation is inspired by nature in order to formulate metaheuristics capable to optimize several kinds of problems. A family of algorithms has emerged based on this idea; e.g. genetic algorithms, evolutionary strategies, particle swarm optimization (PSO), ant colony optimization (ACO), etc. In this paper we show a populationbased metaheuristic inspired on the gravitational forces...

We propose a new nature inspired metaheuristic approach based on the V flight formation of the migrating birds which is proven to be an effective formation in energy saving. Its performance is tested on quadratic assignment problem instances arising from a real life problem and very good results are obtained. The quality of the solutions we report are better than simulated annealing, tabu searc...

The problem of allocating defensive weapon resources to hostile targets is an optimization problem of high military relevance. The need for obtaining the solutions in real-time is often overlooked in existing literature. Moreover, there does not exist much research aimed at comparing the performance of different algorithms for weapon-target allocation. We have implemented a suite of metaheurist...