A three-phase heuristic approach to solve an integrated cell formation and production planning problem

Kheirkhah, Amir Saman; Ghajari, Alireza

doi:10.5267/j.uscm.2017.7.001

Cited by 9 publications

(4 citation statements)

References 21 publications

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“…Further, it has been found that the proposed heuristic algorithm provided a better optimal solution in less computational time. Kheirkhah and Ghajari (2018) proposed a three-phase heuristic algorithm to solve the problem of cellular manufacturing systems and production planning. Further, optimal solutions and computational efficiency were analyzed.…”

Section: Literature Surveymentioning

confidence: 99%

Novel Heuristic Algorithm & its Application for Reliability Optimization

Dahiya,

Vashishth,

Garg

et al. 2023

Int. j. math. eng. manag. sci.

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Heuristic algorithms are practical, easy to implement, and work fast to provide short-term, feasible solutions for any kind of problem within economical budgets as compared to other meta-heuristic algorithms. This paper presents a novel heuristic algorithm named the Dahiya-Garg Heuristic Algorithm (DG-Alg) to find the optimal solution for constrained reliability redundancy allocation optimization problems. The cornerstone of the novel DG-Alg is its novel selection factor, which is a mathematical formula that helps the heuristic algorithm search for optimal subsystems for reliability optimization. A novel formulated selection factor in DG-Alg has increased its effectiveness and efficiency. To analyze the performance of the proposed heuristic algorithm and the other three existing heuristic algorithms, they are applied to a problem taken from a pharmaceutical manufacturing plant named Yaris Pharmaceuticals. During the application of the heuristic algorithms, it was ensured that redundancy allocation was done within stipulated cost constraints. Further, a comparative analysis of the obtained results has been done to judge the performance of the proposed heuristic algorithm. It is deduced that the proposed heuristic algorithm gives optimized and computationally efficient results in comparison to the other existing heuristic algorithms.

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Section: Literature Surveymentioning

confidence: 99%

Novel Heuristic Algorithm & its Application for Reliability Optimization

Dahiya,

Vashishth,

Garg

et al. 2023

Int. j. math. eng. manag. sci.

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“…Flexible manufacturing and heuristic algorithms are two motor themes that were instrumental in defining the field's structure during the initial period. Numerous authors have favored the use of heuristic or meta-heuristic algorithms over mathematical modeling when it comes to solving large CMS problems (Kheirkhah and Ghajari, 2018). Ballakur and Steudel (1987) concluded that the heuristic outperforms multiple criteria.…”

Section: Conceptual Structurementioning

confidence: 99%

Cellular manufacturing system: a descriptive bibliometric analysis, framework, implementation steps and future research direction

Sharma

Nimawat²

2023

BIJ

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PurposeThe purpose of this article is to conduct a bibliometric analysis of the cellular manufacturing system (CMS) literature published from 1982–2021 to identify key issues and trends for the future.Design/methodology/approachA six-stage methodology is used to conduct a literature review, which includes: (1) article collection; (2) inclusion/exclusion criteria; (3) reviewing the articles; (4) analyzing the articles; (5) framework development; and (6) future research directions. A total of 936 CMS-specific articles are reviewed. This paper made use of three software tools: the R package, VOSviewer and SciMAT.FindingsAccording to the findings, the majority of CM researchers focused on cell formation and design. The USA, Iran and India are the top three leading publishers. Additionally, the gap and future direction of CM are discussed.Originality/valueTo the best of the authors' knowledge, the current study is the first attempt to investigate CMS evaluation through bibliometric and thematic analysis and provides a decisional framework as well as steps for CMS adoption. For individuals who are interested in understanding more about CMS and its evolution, this paper offers a starting point.

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“…This avoids the need for a lot of manual water pattern design work, so only a small number of base water patterns need to be designed according to the musical style. Hidden Markov models also applied to chord classification, but they are special in that the observed distribution is no longer based on the given training data set, considering the influence of higher harmonics, using music theory knowledge as a reference for constructing the observation distribution and suggesting that the weight share of fifth-degree chords has more influence compared to third-degree chords [ 10 ]. The final improved model structure and observation distribution allow it to reach 76% in terms of recognition accuracy.…”

Section: Related Workmentioning

confidence: 99%

A Study of Piano-Assisted Automated Accompaniment System Based on Heuristic Dynamic Planning

Lin

Zhao

2022

Computational Intelligence and Neuroscience

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In this paper, a piano-assisted automated accompaniment system is designed and applied to a practical process using a heuristic dynamic planning approach. In this paper, we aim at the generation of piano vocal weaves in accompaniment from the perspective of assisting pop song writing, build an accompaniment piano generation tool through a set of systematic algorithm design and programming, and realize the generation of recognizable and numerous weaving styles within a controlled range under the same system. The mainstream music detection neural network approaches usually convert the problem into a similar way as image classification or sequence labelling and then use models such as convolutional neural networks or recurrent neural networks to solve the problem; however, the existing neural network approaches ignore the music relative loudness estimation subtask and ignore the inherent temporality of music data when solving the music detection task. However, the existing music generation neural network methods have not yet solved the problems of discrete integrability brought by piano roll representation music data and the still-limited control domain and variety of instruments generated in the controllable music generation task. To solve these two problems, this paper proposes a controlled music generation neural network model for multi-instrument polyphonic music. The effectiveness of the proposed model is verified by conducting several sets of experiments on the collected MIDICN data set, and the experimental results show that the model achieves better performance in the aspects of negative log-likelihood value, perplexity, musicality measure, domain similarity analysis, and manual evaluation.

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A three-phase heuristic approach to solve an integrated cell formation and production planning problem

Cited by 9 publications

References 21 publications

Novel Heuristic Algorithm & its Application for Reliability Optimization

Novel Heuristic Algorithm & its Application for Reliability Optimization

Cellular manufacturing system: a descriptive bibliometric analysis, framework, implementation steps and future research direction

A Study of Piano-Assisted Automated Accompaniment System Based on Heuristic Dynamic Planning

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