Hybrid Bat Research Articles

A Swarm Based Hybrid Multipath Load Aware Routing Algorithm for WMN

Background: Wireless Mesh Networks is an emerging field and versatile network infrastructure constitutes the collaboration of heterogeneous mesh routers managed by different users to extend network coverage. The performance of WMNs depends on the designing of a routing protocol. While implementing the routing protocols, allocation of routing metrics are done to different paths for calculating best paths which represents a function for the prediction of the best routing path. Methods: To select best path in WMNs, tree based routing protocols and hop count based routing protocols are proposed earlier. However, Poor scalability and throughput, high overhead owing to control packet flooding are still exists as drawbacks. Moreover, factors namely high number of forwarding nodes and load balancing factor are not focused. A novel routing protocol based on A* path finding algorithm and hybrid BAT algorithm is proposed to solve these issues. There are three phases namely discovery, path selection and route maintenance. In path discovery, the shortest path between the gateway and other nodes is found using A* path finding algorithm where more than five routes have been discovered. In second phase, the best path is selected for data transmission by considering load balancing as an important factor using hybrid BAT algorithm based on path relinking algorithm. During the joining of new nodes or node failures or nodes that are moving continuously in route is maintained through the other two phases. Results: The results of the proposed algorithm is attaining a higher packet delivery ratio, lesser end to end delay and lesser routing overhead than the existing routing protocols such as PAWMNet, FKAWMNet, HBWMnet, and these were obtained from their simulation results. Conclusion: The performances of the proposed algorithm were compared with other existing algorithm using other standard performance metrics which gives best results. The results show that the proposed approach is efficient to determine the parameters which affect the network.

A Novel Hybrid Bat Algorithm with Differential Evolution Strategy for Constrained Optimization

A novel hybrid Bat Algorithm (BA) with the Differential Evolution (DE) strategy using the feasibility-based rules, namely BADE is proposed to deal with the constrained optimization problems. The sound interferences induced by other things are inevitable for the bats which rely on the echolocation to detect and localize the things. Through integration of the DE strategy with BA, the insects’ interferences for the bats can be effectively mimicked by BADE. Moreover, the bats swarm’ mean velocity is simulated as the other bats’ effects on each bat. Having considered the living environments the bats inhabit, the virtual bats can be lifelike. Experiments on some benchmark problems and engineering designs demonstrate that BADE performs more efficient, accurate, and robust than the original BA, DE, and some other optimization methods.

A Hybrid Bat Algorithm for Process Planning Problem

In CAPP, process planning (PP) involves two simultaneous tasks: operations selection and operations sequencing, which is difficult to be carried out to achieve the satisfied process plan. In this paper, a hybrid bat algorithm (BA) has been employed to solve PP problem. To apply BA in PP problem, a 2 x n matrix is proposed to represent the process plan solution. Some strategies of encoding, decoding, population initializing have been developed to adapt the BA algorithm to qualify to solve PP problem. To avoid local convergence, two local search strategies are incorporated into the standard BA. A modification for the local search of BA is executed to improve the bats’ movement. Two new operators for the different parts of the solution representation have been proposed to diversify the bat population. A simulation experiment has been carried out to verify the validity of the hybrid BA. The interesting results show the hybrid BA can generate the satisfactory solutions.

Optimizing a bi-objective inventory model of a three-echelon supply chain using a tuned hybrid bat algorithm

This paper presents a bi-objective VMI problem in a single manufacturer-single vendor multi-retailer (SM-SV-MR) supply chain, which a redundancy allocation problem is incorporated. In the hybridized problem, a manufacturer produces a single item using several machines that work in series, and stores it in a warehouse to replenish one vendor who delivers it to several retailers using the shortest possible route. A novel meta-heuristic, called hybrid bat algorithm (HBA), with calibrated parameters is utilized to find a near-optimum solution. To show the efficiency of HBA, the results are compared to the ones using the traditional BA and a genetic algorithm.

A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical Optimization

A novel robust hybrid metaheuristic optimization approach, which can be considered as an improvement of the recently developed bat algorithm, is proposed to solve global numerical optimization problems. The improvement includes the addition of pitch adjustment operation in HS serving as a mutation operator during the process of the bat updating with the aim of speeding up convergence, thus making the approach more feasible for a wider range of real-world applications. The detailed implementation procedure for this improved metaheuristic method is also described. Fourteen standard benchmark functions are applied to verify the effects of these improvements, and it is demonstrated that, in most situations, the performance of this hybrid metaheuristic method (HS/BA) is superior to, or at least highly competitive with, the standard BA and other population-based optimization methods, such as ACO, BA, BBO, DE, ES, GA, HS, PSO, and SGA. The effect of the HS/BA parameters is also analyzed.

A Hybrid Bat Algorithm with Path Relinking for Capacitated Vehicle Routing Problem

The capacitated vehicle routing problem (CVRP) is an NP-hard problem with wide engineering and theoretical background. In this paper, a hybrid bat algorithm with path relinking (HBA-PR) is proposed to solve CVRP. The HBA-PR is constructed based on the framework of continuous bat algorithm; the greedy randomized adaptive search procedure (GRASP) and path relinking are effectively integrated into bat algorithm. Moreover, in order to further improve the performance, the random subsequences and single-point local search are operated with certain loudness (probability). In order to verify the validity of the method in this paper, and it's efficiency and with other existing methods, several classical CVRP instances from three classes of CVRP benchmarks are selected to tested. Experimental results and comparisons show that the HBA-PR is effective for CVRP.

Smoking and the Need for Vaccination

Modern power system faces excessive frequency aberrations due to the intermittent renewable generations and persistently changing load demands. To avoid any possible blackout, an efficient and robust control strategy is obligatory to minimize deviations in the system frequency and tie-line. Hence, to achieve this target, a new two-degree of freedom-tilted integral derivative with filter (2DOF–TIDN) controller is proposed in this work for a two-area wind-hydro-diesel power system. To enhance the outcome of the proposed 2DOF–TIDN controller, its gain parameters are optimized with the use of a newly designed hybrid bat algorithm-harmony search algorithm (hybrid BA–HSA) technique. The effectiveness and superiority of hybrid BA–HSA tuned 2DOF–TIDN is validated over various existing optimization techniques like cuckoo search (CS), particle swarm optimization (PSO), HSA, BA and teaching learning-based optimization (TLBO). To further refine the system outcome in the dynamic conditions, several flexible AC transmission systems (FACTS) and superconducting magnetic energy storage (SMES) units are adopted for enriching the frequency and tie-line responses. The FACTS controllers like static synchronous series compensator (SSSC), thyristor-controlled phase shifter (TCPS), unified power flow controller (UPFC) and interline power flow controller (IPFC) are employed with SMES simultaneously. The simulation results disclose that the hybrid BA–HSA based 2DOF–TIDN shows superior dynamic performance with IPFC–SMES than other studied approaches. A sensitivity analysis is examined to verify the robustness of proposed controller under ±25% changes in loading and system parameters.