Discrete Cuckoo Search algorithm for job shop scheduling problem

Ouaarab, Aziz; Ahiod, Belaïd; Yang, Xin‐She; Abbad, Mohammed

doi:10.1109/isic.2014.6967636

Cited by 17 publications

(4 citation statements)

References 13 publications

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“…Although the entry-wise product ⊕ employed in PSO is comparable, the random walk via Lévy flight is more effective at navigating the search space since its step length is significantly greater over time. The Lévy flight can exhibit self-similarity and fractal behavior in flight patterns because a power-law distribution is frequently associated with some scale-free properties [16]. Naturally, the Lévy flight is thought to replace the random searching approach of the conventional PSO algorithm in order to improve PSO's performance.…”

Section: Particle Swarm Optimization-cuckoo Search Algorithm With Lév...mentioning

confidence: 99%

PID Control for Nonlinear Processes

Adel,

Bilel,

Abdelkader

2023

PID Control for Linear and Nonlinear Industrial Processes

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This chapter presents a proportional-integral-derivative (PID) Takagi-Sugeno fuzzy system controller that can be trained by the particle swarm optimization-cuckoo search (PSOCS) technique to control nonlinear multi-input multi-output (MIMO) systems. Instead of the standard methods that are widely used in the literature, the PSOCS is used to adjust all of the PID parameters by the minimization of a given objective function. A nonlinear MIMO system has been selected to be controlled by this controller. The simulation results show the notable control accuracy and generalization ability of this MIMO controller. Finally, a comparative study with a PSO algorithm and CS algorithm shows the superiority of the PSOCS over these two optimization methods in terms of guaranteeing the desired performance.

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Section: Particle Swarm Optimization-cuckoo Search Algorithm With Lév...mentioning

confidence: 99%

PID Control for Nonlinear Processes

Adel,

Bilel,

Abdelkader

2023

PID Control for Linear and Nonlinear Industrial Processes

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“…The Lévy flight search is an alternate way of walking with a short distance search combined with occasional longer distance walking [35], which is a random search path and it obeys a Lévy distribution [36], that is a probability distribution proposed by the French mathematician Lévy in the 1930s. Lévy flight can increase the diversity of the population and broaden the scope of the search, which makes it easier to jump out of local optimal points in the intelligent optimization algorithm such as firefly algorithms [37] and cuckoo search [38].…”

Section: Local Search Strategy Based On Lévy Flightmentioning

confidence: 99%

An improved estimation of distribution algorithm for multi-compartment electric vehicle routing problem

Shen

Liwen

2021

J. of Syst. Eng. Electron.

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The multi-compartment electric vehicle routing problem (EVRP) with soft time window and multiple charging types (MCEVRP-STW&MCT) is studied, in which electric multi-compartment vehicles that are environmentally friendly but need to be recharged in course of transport process, are employed. A mathematical model for this optimization problem is established with the objective of minimizing the function composed of vehicle cost, distribution cost, time window penalty cost and charging service cost. To solve the problem, an estimation of the distribution algorithm based on Lévy flight (EDA-LF) is proposed to perform a local search at each iteration to prevent the algorithm from falling into local optimum. Experimental results demonstrate that the EDA-LF algorithm can find better solutions and has stronger robustness than the basic EDA algorithm. In addition, when comparing with existing algorithms, the result shows that the EDA-LF can often get better solutions in a relatively short time when solving medium and large-scale instances. Further experiments show that using electric multi-compartment vehicles to deliver incompatible products can produce better results than using traditional fuel vehicles.

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“…It is mentioned that the entry-wise product ⊕ is similar to that used in PSO, but the random walk via Lévy flight is more efficient in exploring the search space as its step length is much longer in the long run. Because a power-law distribution is often linked to some scale-free characteristics, the Lévy flight can thus show self-similarity and fractal behavior in flight patterns [14]. Naturally, with the purpose of improving the performance of PSO, the Lévy flight is considered to replace the random searching method of traditional PSO algorithm.…”

Section: Particle Swarm Optimization-cuckoo Search Algorithm With Lévmentioning

confidence: 99%

“…The structures and orders of the subsystems have been determined in former research [14,15], ( ( )) = 1 ( ) + . Thus the nonlinear model of the radar turntable servo system can be expressed as…”

Section: Formulation Of the Nonlinear Parameter Identificationmentioning

confidence: 99%

A Hybrid Particle Swarm Optimization-Cuckoo Search Algorithm and Its Engineering Applications

Ding

Wang

Zhang

et al. 2019

Mathematical Problems in Engineering

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This paper deals with the hybrid particle swarm optimization-Cuckoo Search (PSO-CS) algorithm which is capable of solving complicated nonlinear optimization problems. It combines the iterative scheme of the particle swarm optimization (PSO) algorithm and the searching strategy of the Cuckoo Search (CS) algorithm. Details of the PSO-CS algorithm are introduced; furthermore its effectiveness is validated by several mathematical test functions. It is shown that Lévy flight significantly influences the algorithm’s convergence process. In the second part of this paper, the proposed PSO-CS algorithm is applied to two different engineering problems. The first application is nonlinear parameter identification for the motor drive servo system. As a result, a precise nonlinear Hammerstein model is obtained. The second one is reactive power optimization for power systems, where the total loss of the researched IEEE 14-bus system is minimized using PSO-CS approach. Simulation and experimental results demonstrate that the hybrid optimal algorithm is capable of handling nonlinear optimization problems with multiconstraints and local optimal with better performance than PSO and CS algorithms.

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Discrete Cuckoo Search algorithm for job shop scheduling problem

Cited by 17 publications

References 13 publications

PID Control for Nonlinear Processes

PID Control for Nonlinear Processes

An improved estimation of distribution algorithm for multi-compartment electric vehicle routing problem

A Hybrid Particle Swarm Optimization-Cuckoo Search Algorithm and Its Engineering Applications

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