Ant colony optimisation algorithms for two-stage permutation flow shop with batch processing machines and nonidentical job sizes

鄭, 旭光; Zhou, Shengchao

doi:10.1080/00207543.2018.1529445

Cited by 19 publications

(6 citation statements)

References 70 publications

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“…Transmission lines bear the heavy responsibility of transmitting electrical energy and are the most extensively distributed component of the power grid [1,2]. With the gradual construction of the power grid, the total length of long-distance, large-capacity AC and DC transmission lines of various voltage levels are gradually increasing.…”

Section: Introductionmentioning

confidence: 99%

Research on Transmission Line Fault Location Based on the Fusion of Machine Learning and Artificial Intelligence

Liu

2021

Security and Communication Networks

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After a transmission line fails, quickly and accurately find the fault point and deal with it, which is of great significance to maintaining the normal operation of the power system. Aiming at the problems of low accuracy of traditional traveling wave fault location methods and many affected factors, this paper relies on distributed traveling wave monitoring points arranged on transmission lines to study methods to improve the accuracy of traveling wave fault location on transmission lines. First, when a line fails, a traveling wave signal that moves to both ends will be generated and transmitted along the transmission line. We use the Radon transform algorithm to process the traveling wave signal. Then, this paper uses ant colony algorithm to analyze and verify the location and extent of transmission line faults and then optimizes high-precision collection and processing. Finally, the simulation distance measurement is carried out on double-terminal transmission lines and multiterminal transmission lines (T-shaped lines) with branches. The results show that, for double-ended transmission lines, the algorithm increases the speed of matrix calculations and at the same time makes the fault location error of the transmission grid still maintain the improved effect.

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Section: Introductionmentioning

confidence: 99%

Research on Transmission Line Fault Location Based on the Fusion of Machine Learning and Artificial Intelligence

Liu

2021

Security and Communication Networks

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“…Since then, different approaches have been proposed to enrich line balance analyses, and many attempts have been made to reduce the wide gap between the academic discussion and the realistic situation". In 2018, during a bibliometric study carried out on the Web of Science by Zheng, Zhou, and Chen (2019), it was found that, until that date, there had been more than 2476 published research results aimed at optimizing production flows. These studies (Kucukkoc, Li, Karaoglan, & Zhang, 2018;Tanhaie, Rabbani, & Manavizadeh, 2020) generally seek to optimize the use of installed capacities, increase productivity, reduce cycle time , reduce the number of jobs, reduce energy consumption, reduce environmental pollution (Kalayci & Gupta, 2013), and reduce the learning cost curve (Wu, Dai, & Luo, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

Unlocking the power of investment decision making with MATLAB: A cutting-edge method for optimizing capacities

Perez-Campdesuner,

Sanchez-Rodriguez,

Garcia-Vidal

et al. 2023

Nurture

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Purpose: The aim of this research was to present a method that would allow responding to both interests in a staggered and proportional way, in correspondence with existing financial availability. Design/Methodology/Approach: This research shows the results of the application of a methodological proposal programmed in MATLAB, which provided a solution to the described problem. Findings: The application was carried out in a small company, which has three fundamental products, and allowed to optimize the use of the available capital, increasing both the installed capacities and the potential demand for the products offered. Conclusion: It is possible to define an investment strategy that, based on the existence of an amount of financial availability, alternates the investment in the limiting capacity or the commercialization actions in correspondence with what is the limitation of the organization, which can be a limitation of capacity or market. This favors a systematic increase in the utility of the organization. Practical Implications: An analysis algorithm is developed that can serve as a guide for businessmen to design investment strategies aimed at increasing demand or capacity restrictions, as the case may be, based on financial availability and contributing to the systematic increase in the utility of the organization under study. Contribution to Literature: A method is presented that combines the analysis of capacity restrictions with those of demand restrictions, an aspect that is generally addressed in the literature independently.

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“…Static AGV scheduling denotes an NP-hard problem. Numerous studies indicate that the heuristic algorithm can effectively solve an NP-hard problem, such as simulated annealing algorithm (SAA), 23 genetic algorithm (GA), 24 ant colony optimization (ACO), 25 and artificial neural network (ANN). 26 Mousavi et al 27 developed a mathematical model and integrated it with evolutionary algorithms (GA, particle swarm optimization (PSO), and hybrid GA-PSO) to optimize the task scheduling of AGVs with the objectives of minimizing makespan and number of AGVs while considering the AGVs’ battery charge.…”

Section: Literature Reviewmentioning

confidence: 99%

A bio-inspired scheduling approach for machines and automated guided vehicles in flexible manufacturing system using hormone secretion principle

Zheng

et al. 2020

Advances in Mechanical Engineering

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The product quality and production efficiency of a flexible manufacturing system have improved effectively by introducing the computer management and the material transportation system. The flexible manufacturing system performance greatly depends on the performance of the material transportation system. As a mobile robot controlled by a central controller, an automated guided vehicle has a strong ability for material transportation. This article studies a dynamic scheduling problem in a shop floor, where machines and automated guided vehicles run at a specified speed and specifies a mathematical model for the dynamic scheduling problem with the goal of makespan minimization. Meanwhile, inspired by the hormone secretion principle of the endocrine system, a bio-inspired scheduling optimization approach is developed to solve the dynamic scheduling problem in the flexible manufacturing system. To verify its practical application, the bio-inspired scheduling optimization approach and other scheduling approaches are tested, and the results illustrate that the bio-inspired scheduling optimization approach has better scheduling performance as well as optimizes the quality of integrated and real-time scheduling of machines and automated guided vehicles.

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Ant colony optimisation algorithms for two-stage permutation flow shop with batch processing machines and nonidentical job sizes

Cited by 19 publications

References 70 publications

Research on Transmission Line Fault Location Based on the Fusion of Machine Learning and Artificial Intelligence

Research on Transmission Line Fault Location Based on the Fusion of Machine Learning and Artificial Intelligence

Unlocking the power of investment decision making with MATLAB: A cutting-edge method for optimizing capacities

A bio-inspired scheduling approach for machines and automated guided vehicles in flexible manufacturing system using hormone secretion principle

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