To address issues such as poor initial population diversity, low stability and local convergence accuracy, and easy local optima in the traditional multi-objective artificial hummingbird algorithm (MOAHA), an Improved...
详细信息
To address issues such as poor initial population diversity, low stability and local convergence accuracy, and easy local optima in the traditional multi-objective artificial hummingbird algorithm (MOAHA), an Improved MOAHA (IMOAHA) was proposed. The improvements involve Tent mapping based on random variables to initialize the population, a logarithmic decrease strategy for inertia weight to balance search capability, and the improved search operators in the territory foraging phase to enhance the ability to escape from local optima and increase convergence accuracy. The effectiveness of IMOAHA was verified through Matlab/Simulink. The results demonstrate that IMOAHA exhibits superior convergence, diversity, uniformity, and coverage of solutions across 6 test functions, outperforming 4 comparative algorithms. A Wilcoxon rank-sum test further confirmed its exceptional performance. To assess IMOAHA’s ability to solve engineering problems, an optimization model for a multi-track, multi-train urban rail traction power supply system with Supercapacitor Energy Storage Systems (SCESSs) was established, and IMOAHA was successfully applied to solving the capacity allocation problem of SCESSs, demonstrating that it is an effective tool for solving complex multi-objective Optimization Problems (MOOPs) in engineering domains.
For stabilizing a nonlinear ball-wheel system, this research suggests a fuzzy fractional-order adaptive robust feedback linearization control approach. The feedback linearization-based controller uses the decoupled sl...
详细信息
For stabilizing a nonlinear ball-wheel system, this research suggests a fuzzy fractional-order adaptive robust feedback linearization control approach. The feedback linearization-based controller uses the decoupled sliding mode to locate the sliding surfaces and determine the adaptive coefficients. Then, the fractional-order calculus and fuzzy logic-based systems are implemented to improve the efficiency of the controller. Additionally, the multi-objective artificial hummingbird algorithm (MAHA) is employed to optimize the control coefficients by including two objective functions, namely the integral of the absolute values of the control efforts and the system errors. The success of the suggested strategy is then evaluated by applying it on the ball-wheel system and comparing the outcomes to those documented in the literature.
PurposeThis study aims to optimize the construction site layout planning (CSLP) problem, with a focus on prefabricated projects. It proposes the use of the oMOAHA algorithm, an enhanced version of the multi-objective ...
详细信息
PurposeThis study aims to optimize the construction site layout planning (CSLP) problem, with a focus on prefabricated projects. It proposes the use of the oMOAHA algorithm, an enhanced version of the multi-objective artificial hummingbird algorithm (MOAHA), to address challenges related to search space exploration and local optimization in ***/methodology/approachThe study integrates three techniques - opposition-based learning (OBL), quasi-opposition and quasi-reflection - into the initialization phase of the MOAHA algorithm, creating the oMOAHA variant. This model is applied to all three types of CSLP problems - pre-determined location, grid system and continuous space - to evaluate its effectiveness. Six objective functions (three related to cost, two to safety and one to tower crane efficiency) and four site-related constraints are considered through three case studies taken from previous research and one real project involving prefabricated steel *** oMOAHA algorithm demonstrates superior performance compared to previous models, consistently outperforming traditional approaches in CSLP optimization for prefabricated projects. In the real case study, the proposed model exceeded the actual project plan by 28-43%, indicating its potential to significantly improve both solution quality and project ***/valueThis study is the first to apply an optimization model to all three types of CSLP problems - pre-determined location, grid system and continuous space - within a unified framework. The integration of advanced techniques into the MOAHA algorithm and the model's successful application in a real prefabricated project underscore its high applicability and effectiveness in modern construction management.
multi-functional grid connected inverter (MFGCI) has the ability to solve various power quality problems in the distribution network while fulfilling the power tracking task simultaneously, but this ability is often l...
详细信息
暂无评论