Combining ant colony optimization (ACO) and multiobjective evolutionary algorithm based on decomposition (MOEA/D), this paper proposes a multiobjective evolutionary algorithm, MOEA/D-ACO. Following other MOEA/D-like algorithms, MOEA/D-ACO decomposes an multiobjective optimization problem into a number of single objective optimization problems. Each ant (i.e. agent) is responsible for solving on...

This paper proposes an efficient load frequency control (LFC) technique based on a fractional-order proportional–integral–derivative–accelerator with low-pass filter compensator (FOPIDA-LPF) controller, which can also be accurately referred to as the PIλDND2N2 controller. A trustworthy metaheuristic optimization algorithm, known gray wolf optimizer (GWO), is used fine-tune suggested controller ...

The heap-based optimizer (HBO) is an innovative meta-heuristic inspired by human social behavior. In this research, binary adaptations of the B_HBO are presented and used to determine optimal features for classifications in wrapping form. addition, HBO balances exploration exploitation employing self-adaptive parameters that can adaptively search solution domain solution. feature selection doma...

In recent decades, Renewable Energy Sources (RES) have become more attractive due to the depleting fossil fuel resources and environmental issues such as global warming emissions from fuel-based power plants. However, intermittent nature of RES may cause a imbalance between generation demand. The is overcome with help Distributed Generators (DG), storage devices, RES. aggregation DGs, controlla...

The Multi-Depot Vehicle Routing Problem (MDVRP) is a generalization of SDVRP, in which multiple vehicles start from multiple depots and return to their original depots at the end of their assigned tours. The MDVRP is NP-hard, therefore, the development of heuristic algorithms for this problem class is of primary interest. This paper solves Multi-Depot Vehicle Routing Problem with Cellular Ant A...

Original scientific paper Routing is one of the most important problems in Mobile Ad-hoc Networks (MANETs). Various techniques have been developed to cope with this problem. Ant-based routing is optimization technique used commonly. Ant-based routing is derived from ant colony optimization, which was inspired by ants. This article recommends a load balancing scheme based on the ant colony. The ...

The significance of accurate heating load (HL) approximation is the primary motivation this research to distinguish most efficient predictive model among several neural-metaheuristic models. proposed models are formulated through synthesizing a multi-layer perceptron network (MLP) with ant lion optimization (ALO), biogeography-based (BBO), dragonfly algorithm (DA), evolutionary strategy (ES), i...

This paper proposed an optimization method to minimize the building energy consumption and visual discomfort for a passive in Shanghai, China. A total of 35 design parameters relating form, envelope properties, thermostat settings, green roof configurations were considered. First, Latin hypercube sampling (LHSM) was used generate set samples, samples obtained through computer simulation calcula...

Airport public transport systems are plagued by passenger queue congestion, imposing a substandard travel experience and unexpected delays. To address this issue, paper proposes bi-level programming for optimizing queueing network in airport access based on choice behavior. For purpose, we derive system, which include the taxi, bus, subway. Then, propose model network. The lower level subprogra...

Ant colony optimization is a well known metaheuristic which has been object of many studies, both theoretic and applicative. In a recent analysis [1], a particular aspect of its behavior is investigated. More in detail, the topic object of interest is the result achieved by ant algorithms when the cost unit in which instances are expressed changes. Three ant colony optimization algorithms are p...