A meta-heuristic method for solving scheduling problem: crow search algorithm

Adhi, Antono; Santosa, Budi; Siswanto, Nurhadi

doi:10.1088/1757-899x/337/1/012003

Cited by 18 publications

(9 citation statements)

References 13 publications

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“…Based on the literature review, some implementations use different values for population size, awareness probability and flight length (Souza et al, 2018;Islam et al, 2020). On the other hand, Adhi et al (2018) and Majhi et al (2020) tuned the lower and upper boundaries for their applications. Due to the inconsistencies of the parameter setting in the previous works, all parameters were considered and observed in this analysis.…”

Section: Resultsmentioning

confidence: 99%

A Single Objective Crow Search for Modelling of Horizontal Flexible Plate Structure

Shaari¹,

Hadi²,

Wahab³

2023

JST

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The magnificent features of flexible plate structure, including lightweight and high-speed response, resulted in additional market demand, especially in the automotive and manufacturing industries. Nevertheless, the structure may incur structural damage and performance degradation when the system encounters excessive vibration. Therefore, a system identification approach utilising a metaheuristic algorithm via crow search to develop a horizontal flexible plate (HFP) model for vibration control is introduced in this paper. Crow search (CS) is a modern algorithm inspired by a crow’s intellectual operation to store additional food and memorise the food storage location. In this study, CS is employed to optimise the objective function, which is the mean squared error for accomplishing a precise predicted model in replicating the dynamic response of the actual structure. Hence, the preliminary action for modelling using this approach is designing and fabricating an HFP rig for experimentally gathering the real input-output vibration data. After that, the mathematical modelling utilising the CS algorithm was implemented using a parametric model structure. Finally, the best-fit model is chosen for the representation of the HFP based on the lowest mean squared error, correlation test within a 95% confidence level and stability in a pole-zero plot. The simulation result reveals that the CS algorithm with a second-order estimated model accomplished a minimum MSE of 1.1168 × 10-5, an unbiased correlation test and excellent stability for the HFP structure.

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Section: Resultsmentioning

confidence: 99%

A Single Objective Crow Search for Modelling of Horizontal Flexible Plate Structure

Shaari¹,

Hadi²,

Wahab³

2023

JST

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“…Authors in Baker [15], Morton et al, [16], and Pinedo [17] defined that "scheduling is a process associated with the allocation of sources to perform the task within a period of time". It has been widely utilized on the various field in real-world problem including manufacturing and services [18], satellite broadcast scheduling problem [19], academic scheduling problems [20], energy management [21], and engineering field [22]. Scheduling also involves many components including the distribution of available resources for tasks or activities over time.…”

Section: Meta-heuristic Algorithm For the Scheduling Problemmentioning

confidence: 99%

“…However, in many scenarios, the optimization problem provides the most problematic and it becomes NP-hard problem [18]. NP-hard stands for a non-deterministic polynomial-time hardness where the problem has no known polynomial algorithm, then, the finding solution time is increased simultaneously with problem size.…”

Section: Meta-heuristic Algorithm For the Scheduling Problemmentioning

confidence: 99%

Methodology for Modified Whale Optimization Algorithm for Solving Appliances Scheduling Problem

Omar

Bakeri

Nawi

et al. 2020

ARFMTS

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Whale Optimization Algorithm (WOA) is considered as one of the newest metaheuristic algorithms to be used for solving a type of NP-hard problems. WOA is known of having slow convergence and at the same time, the computation of the algorithm will also be increased exponentially with multiple objectives and huge request from n users. The current constraints surely limit for solving and optimizing the quality of Demand Side Management (DSM) case, such as the energy consumption of indoor comfort index parameters which consist of thermal comfort, air quality, humidity and vision comfort. To address these issues, this proposed work will firstly justify and validate the constraints related to the appliances scheduling problem, and later proposes a new model of the Cluster based Multi-Objective WOA with multiple restart strategy. In order to achieve the objectives, different initialization strategy and cluster-based approaches will be used for tuning the main parameter of WOA under different MapReduce application which helps to control exploration and exploitation, and the proposed model will be tested on a set of well-known test functions and finally, will be applied on a real case project i.e. appliances scheduling problem. It is anticipating that the approach can expedite the convergence of meta-heuristic technique with quality solution.

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“…The literature shows that some multiobjective algorithms help reduce greenhouse gases while decreasing fuel costs at the same time. These algorithms include scatter search [4], the bacterial foraging algorithm [5], particle swarm optimization [6], teaching-learning-based optimization [7], the harmony search algorithm [8], and differential evolution [9].…”

Section: Introductionmentioning

confidence: 99%

“…In this case, the "h" parameter is used to handle dimensional problems that can be solved through the sketched evolutionary algorithm [8]- [10]. We can also solve the CEED problem without using the mentioned parameter by regularizing fuel costs and pollutants.…”

Section: Introductionmentioning

confidence: 99%

Optimal Sizing of a Renewable Energy Hybrid System in Libya Using Integrated Crow and Particle Swarm Algorithms

Elbaz¹,

Guneser²

2020

Adv. sci. technol. eng. syst. j.

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Sizing optimization should be used to design an efficient, sustainable, and feasible hybrid system. In this paper, a hybrid power plant consisting of an off-grid photovoltaic and wind energy system was planned to supply the demand of residential houses in Libya. To minimize installation and operational costs by sizing each part of the hybrid system, the crow search technique was applied. We optimized the number of photovoltaic modules, wind turbine power, and battery capacity and then we compared the performance of the crow algorithm with the particle swarm optimization algorithm for hybrid system design. The results of the crow algorithm suggest better efficiency for sizing lower-cost hybrid power plants consisting of photovoltaic and wind systems.

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A meta-heuristic method for solving scheduling problem: crow search algorithm

Cited by 18 publications

References 13 publications

A Single Objective Crow Search for Modelling of Horizontal Flexible Plate Structure

A Single Objective Crow Search for Modelling of Horizontal Flexible Plate Structure

Methodology for Modified Whale Optimization Algorithm for Solving Appliances Scheduling Problem

Optimal Sizing of a Renewable Energy Hybrid System in Libya Using Integrated Crow and Particle Swarm Algorithms

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