This study proposes a novel strength of multi-objective gravitational search algorithm and bat algorithm MOGSABAT to solve multi-objective optimisation problem. The proposed MOGSABAT algorithm is divided into three st...
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This study proposes a novel strength of multi-objective gravitational search algorithm and bat algorithm MOGSABAT to solve multi-objective optimisation problem. The proposed MOGSABAT algorithm is divided into three stages. In the first stage (moving space), a switch in a solution from single function to multiple functions that contain more than one objective to use the gravitational search algorithm GSA is determined. We established a new equation to calculate the masses of individuals in the population using the theoretical work found in the strength Pareto evolutionary algorithm. In the second stage (moving in space), how to handle the bat algorithm BAT to solve multiple functions is established. We applied the theoretical work of multi-objective particle swarm optimisation into the BAT algorithm to solve multiple functions. In the third stage, multi-objective GSA and multi-objective BAT are integrated to obtain the hybrid MOGSABAT algorithm. MOGSABAT is tested by adopting a three-part evaluation methodology that (1) describes the benchmarking of the optimisationproblem (bi-objective and tri-objective) to evaluate the performance of the algorithm;(2) compares the performance of the algorithm with that of other intelligent computation techniques and parameter settings;and (3) evaluates the algorithm based on mean, standard deviation and Wilcoxon signed-rank test statistic of the function values. The optimisation results and discussion confirm that the MOGSABAT algorithm competes well with advanced metaheuristic algorithms and conventional methods.
Material transportation scheduling problems concerning scheduling optimisation have been extensively investigated by researchers in such fields as industrial engineering and management science. Various algorithms have...
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Material transportation scheduling problems concerning scheduling optimisation have been extensively investigated by researchers in such fields as industrial engineering and management science. Various algorithms have been proposed to solve such problems. However, the majority of these algorithms cannot be applied to a block transportation problem when a shipyard that uses a transporter, a large vehicle employed for moving weight, is considered. In this study, a hybrid optimisation algorithm is proposed for solving a block transportation problem when multiple transporters are used. With regards to the transporters, a minimisation of the travel distance without loading of and interference between the transporters is considered. A block transportation scheduling system is then developed based on the proposed algorithm. The developed system is applied to an actual block transportation scheduling problem of a shipyard. From the attained results, we demonstrate that the proposed algorithm has the ability to effectively solve the block transportation scheduling problems of a shipyard.
Previous investigations indicated that a flat-walled, multi-layered anechoic lining system, with an overall thickness slightly less than a quarter of a wavelength, could be used to achieve a required cut-off frequency...
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Previous investigations indicated that a flat-walled, multi-layered anechoic lining system, with an overall thickness slightly less than a quarter of a wavelength, could be used to achieve a required cut-off frequency. However, the work proved to be tedious and time consuming because of the numerous trial-and-error measurements involved. On the other hand, the successful application of a method of calculating the overall acoustic impedance of multi-layered absorbing systems has indicated that the design of multi-layered absorbing systems can be carried out on a desktop computer. In the present work, a MATLAB genetic and evolutionary algorithm toolbox is implemented as the optimiser to aid and speed up the design process. The optimisation results indicate that a three-layered lining system can achieve results comparable with quality wedge-type anechoic linings with overall thickness slightly less than a sixth of a wavelength at the 100 Hz cut-off frequency. (C) 2004 Elsevier Ltd. All rights reserved.
Real-world problems often comprise multiple interdependent sub-problems. The interdependency between sub-problems makes the original problem complex. The Travelling Thief problem (TTP), an exemplary representation of ...
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Real-world problems often comprise multiple interdependent sub-problems. The interdependency between sub-problems makes the original problem complex. The Travelling Thief problem (TTP), an exemplary representation of such a multi-component optimisationproblem, is introduced in the literature with sheer academic interest. TTP, a combination of the Travelling Salesman problem and the Knapsack problem, has drawn much attention over the past few years. Several variants of TTP have also been developed and studied extensively. The literature around TTP has been increasing consistently. This growing interest motivates us to present a systematic overview of the existing literature. To the best of our knowledge, this is the first attempt towards a systematic literature review on TTP. This paper surveys TTP, Packing While Travelling (PWT), Thief Orienteering problem (ThOP), and their associated operations, analysing 68 articles. With the evolution of logistics, TTP and ThOP find more relevance in pick-up and delivery services (including courier $ \& $ & recyclable-goods collection). The study comprehensively covers TTP variants (i.e. mono $ \& $ & bi-objective TTP, multiple $ \& $ & dynamic TTP, PWT) and ThOP. Subsequently, state-of-the-art TTP and ThOP solution methodologies are reviewed and classified into exact, heuristic, meta-heuristic, and hyper-heuristic methods. Finally, research gaps and future research opportunities are delineated for TTP and ThOP.
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