Hybrid optimization algorithms by various structures for a real-world inverse scheduling problem with uncertain due-dates under single-machine shop systems

Mou, Jianhui; Gao, Liang; Guo, Qianjian; Xu, Renjie; Li, Xinyu

doi:10.1007/s00521-018-3472-7

Cited by 14 publications

(2 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Koulamas [13] explored the inverse JSP with controllable makespan based on Johnson's rule. Mou et al [14] studied the modelling and solution of inverse JSP, converted the problem into different mathematical forms, and presented a solution with no weight and minimal makespan. Peng et al [15] attempted to minimize the total weighted makespan of the inverse JSP for parallel machines, and obtained the optimal solution by linear programming and quadratic programming.…”

Section: Literature Reviewmentioning

confidence: 99%

A Solution to Single-Machine Inverse Job-Shop Scheduling Problem

Wang¹,

Yang²,

Wang³

2019

Int. j. simul. model.

View full text Add to dashboard Cite

Concerning the inverse job-shop scheduling problem (JSP), this paper proposes a hybrid solution based on genetic algorithm (GA) and improved particle swarm optimization (PSO), with the aim to minimize the parameter adjustment. The solution was presented as a block coding plan with decimal mechanism, under which both processes and parameters can be optimized simultaneously. To enhance the local search ability of the proposed algorithm, four neighbourhood structures were designed, and an adaptive selection mechanism was created to select the most suitable neighbourhood. Finally, the proposed algorithm was proved valid through discrete event simulation (DES) and comparison with other algorithms.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

A Solution to Single-Machine Inverse Job-Shop Scheduling Problem

Wang¹,

Yang²,

Wang³

2019

Int. j. simul. model.

View full text Add to dashboard Cite

show abstract

“…Different authors described applications of IFSs and PFSs in decision-making [3,6,15,26]. For further studies, the readers are referred to [5,16,23,29,32].…”

Section: Introductionmentioning

confidence: 99%

An algorithm to compute the strength of competing interactions in the Bering Sea based on pythagorean fuzzy hypergraphs

Nawaz

Akram

Alcantud

2021

Neural Comput & Applic

View full text Add to dashboard Cite

The networks of various problems have competing constituents, and there is a concern to compute the strength of competition among these entities. Competition hypergraphs capture all groups of predators that are competing in a community through their hyperedges. This paper reintroduces competition hypergraphs in the context of Pythagorean fuzzy set theory, thereby producing Pythagorean fuzzy competition hypergraphs. The data of real-world ecological systems posses uncertainty, and the proposed hypergraphs can efficiently deal with such information to model wide range of competing interactions. We suggest several extensions of Pythagorean fuzzy competition hypergraphs, including Pythagorean fuzzy economic competition hypergraphs, Pythagorean fuzzy row as well as column hypergraphs, Pythagorean fuzzy k-competition hypergraphs, m-step Pythagorean fuzzy competition hypergraphs and Pythagorean fuzzy neighborhood hypergraphs. The proposed graphical structures are good tools to measure the strength of direct and indirect competing and non-competing interactions. Their aptness is illustrated through examples, and results support their intrinsic interest. We propose algorithms that help to compose some of the presented graphical structures. We consider predator-prey interactions among organisms of the Bering Sea as an application: Pythagorean fuzzy competition hypergraphs encapsulate the competing relationships among its inhabitants. Specifically, the algorithm which constructs the Pythagorean fuzzy competition hypergraphs can also compute the strength of competing and non-competing relations of this scenario.

show abstract

Special issue on emergence in human-like intelligence toward cyber-physical systems

Yen

2019

Neural Comput & Applic

View full text Add to dashboard Cite

As the famous slogan ''Connecting People'' indicates, a lot of the developments in novel technologies intensify the relationship between people without necessarily enhancing technologies that are close to the nature of human beings. Examples can be easily found in recent computing paradigms, such as Cloud Computing that advances network infrastructure for data storage and resource sharing, or the Internet of Things that investigates the intelligence and awareness of objects involved in the network. From this point of view, the existing state-of-the-art solutions, in realms of artificial intelligence and/or computational intelligence, significantly differ from the human competence level in many research domains. Even though it is generally not clear whether human-like approach would show its upper-hand over existing methods, the exploration of this research path seems to be advantageous and challenging. Human-like intelligence is arguably one of the most powerful approaches for the optimization and design of complex Web, as well as its correlated issues so as to meet the requirements and growing needs of new challenging applications (and services as well). Although the state of the art behind the computational intelligence has already reached an impressive scale, there remain quite a lot of attractive research topics, with consideration of human-like or human-oriented factors, for further and promising developments.The submitted manuscripts were reviewed by experts from both academia and industry. After two rounds of reviewing, the highest quality manuscripts were accepted for this special issue. This special issue will be published by Neural Computing and Applications as special issues.

show abstract

Hybrid optimization algorithms by various structures for a real-world inverse scheduling problem with uncertain due-dates under single-machine shop systems

Cited by 14 publications

References 29 publications

A Solution to Single-Machine Inverse Job-Shop Scheduling Problem

A Solution to Single-Machine Inverse Job-Shop Scheduling Problem

An algorithm to compute the strength of competing interactions in the Bering Sea based on pythagorean fuzzy hypergraphs

Special issue on emergence in human-like intelligence toward cyber-physical systems

Contact Info

Product

Resources

About