An effective adaptive iterated greedy algorithm for a cascaded flowshop joint scheduling problem

Wang, Chuang; Pan, Quan-Ke; Jing, Xue-Lei

doi:10.1016/j.eswa.2023.121856

Cited by 5 publications

(2 citation statements)

References 54 publications

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“…The greedy algorithm [9], serving as a local search algorithm, plays a crucial role in this study. The fundamental idea of the greedy algorithm is to choose the locally optimal solution at each step, with the expectation of ultimately obtaining a globally optimal solution.…”

Section: Research Methodolpgymentioning

confidence: 99%

Optimization of Multibeam Survey Measurement Based on Greedy Algorithm

Zhang

2024

HSET

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The effectiveness of multibeam bathymetric technology is widely recognized in marine depth measurements, especially in areas with complex and variable seafloor topography. This study aims to design a multibeam bathymetric survey plan for a specific maritime region, with the objectives of minimizing the total survey line length, ensuring comprehensive coverage of the target area, controlling the overlap between adjacent survey lines, and fully considering variations in seafloor topography. An optimization model was developed to determine the optimal route for comprehensive seafloor depth measurements within the specified maritime area.The model initially considers the influence of seafloor slope, establishing a single optimization objective model with the goal of minimizing the total survey line length. The decision variables primarily include the spacing between adjacent survey lines. The objective function of the model aims to reduce the number of survey lines, thereby achieving the minimization of the total survey line length. Constraints of the model encompass limitations on coverage range, calculations of coverage width, and relationships between survey lines. The model is solved using a greedy algorithm-based optimization approach, iteratively updating the positions of survey lines while determining the spacing based on the relationship between depth and coverage width. Ultimately, a layout of survey lines with the shortest total length, totaling 64 nautical miles with a configuration of 32 survey lines, is obtained for the assumed maritime area. Multibeam bathymetric technology holds broad prospects in the field of marine measurements, particularly in areas characterized by complex and variable seafloor topography. This study, by designing a multibeam bathymetric survey plan for a specific maritime region, not only contributes to improving measurement efficiency and accuracy but also reduces measurement costs and resource consumption. The outcomes of this research have significant practical implications for marine resource development, seafloor engineering construction, environmental protection, providing professionals in related fields with an effective measurement method and optimization strategy.

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Section: Research Methodolpgymentioning

confidence: 99%

Optimization of Multibeam Survey Measurement Based on Greedy Algorithm

Zhang

2024

HSET

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“…The flowshop layout is also commonly used in manufacturing systems, where production machines are arranged based on product production routing [7], [8]. A production system with a fellowship configuration exhibits limited flexibility, necessitating serial or multiple flow shop systems [9] or creating a new production line tailored to the new products. A conveyor with a linear flow is the typical material handling equipment employed in production systems with a flow shop layout.…”

Section: Introductionmentioning

confidence: 99%

Intelligent optimisation for multi-objectives flexible manufacturing cells formation

Purnomo,

Widodo,

Zukhri

2024

j. sist. manaj. ind.

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The primary objective of conventional manufacturing cell formation typically uses grouping efficiency and efficacy measurement to reduce voids and exceptional parts. This objective frequently leads to extreme solutions, such as the persistently significant workload disparity among the manufacturing cells. It will have a detrimental psychological impact on operators who work in each formed manufacturing cell. The complexity of the problem increases when there is a requirement to finish all parts before the midday break, at which point the formed manufacturing cells can proceed with the following production batch after the break. This research examines the formation of manufacturing cells using two widely recognized intelligent optimization techniques: genetic algorithm (G.A.) and particle swarm optimisation (PSO). The discussed manufacturing system has flexible machines, allowing each part to have multiple production routing options. The optimisation process involved addressing four simultaneous objectives: enhancing the efficiency and efficacy of the manufacturing cells, minimizing the deviation of manufacturing cells working time with the allocated working hours, which is prior to the midday break, and ensuring a balanced workload for the formed manufacturing cells. The optimisation results demonstrate that the G.A. outperforms the PSO method and is capable of providing manufacturing cell formation solutions with an efficiency level of 0.86, efficacy level as high as 0.64, achieving a minimum lateness of only 24 minutes from the completion target before midday break and a maximum difference in workload as low as 49 minutes.

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