Efficient optimization of multi-objective redundancy allocation problems in series-parallel systems

Arjestan, Mina Ebrahimi

doi:10.5267/j.dsl.2016.11.004

Cited by 3 publications

(1 citation statement)

References 24 publications

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“…But there is an important issue here is how it can be argued that the proposed method, this is an effective method. To answer this question it is necessary to use several methods to assess the suitability of the results they achieved an overall result (Arjestan, 2016) The intense growth in products variety and competitions between firms leads firms to produce more customized product according to customers' requirements. However, this will increase productions cost and products delivery time to customers as well.…”

Section: Conclusion and Future Research Directionsmentioning

confidence: 99%

Determining decoupling points in a supply chain networks using NSGA II algorithm

Ebrahimiarjestan¹,

Wang²

2017

JIEM

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Abstract:Purpose: In the model, we used the concepts of Lee and Amaral (2002) and Tang and Chen (2009) and offer a multi-criteria decision-making model that identify the decoupling points to aim to minimize production costs, minimize the product delivery time to customer and maximize their satisfaction.Design/methodology/approach: we encounter with a triple-objective model that metaheuristic method (NSGA II) is used to solve the model and to identify the Pareto optimal points.The max (min) method was used.Findings: Our results of using NSGA II to find Pareto optimal solutions demonstrate good performance of NSGA II to extract Pareto solutions in proposed model that considers determining of decoupling point in a supply network. Originality/value: So far, several approaches to model the future have been proposed, of course, each of them modeled a part of this concept. This concept has been considered more general in the model that defined in follow. In this model, we face with a multi-criteria decision problem that includes minimization of the production costs and product delivery time to customers as well as customer consistency maximization.-352-Journal of Industrial Engineering and Management -https://doi

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Section: Conclusion and Future Research Directionsmentioning

confidence: 99%

Determining decoupling points in a supply chain networks using NSGA II algorithm

Ebrahimiarjestan¹,

Wang²

2017

JIEM

View full text Add to dashboard Cite

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Efficient optimization of multi-objective redundancy allocation problems in series-parallel systems

Arjestan¹

2017

10.5267/j.dsl

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Maintenance policy selection of n-component repairable system using Genetic Algorithm

Srivastava¹,

Kuila²,

Chatterjee³

et al. 2022

Serb J Management

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A typical manufacturing system consists of a large number of repairable components/ machines which age with time and require maintenance. This paper proposes a novel maintenance policy selection method using genetic algorithm. Where, maintenance problem is formulated for n-component repairable system to minimize the total maintenance cost. The various maintenance policies and repairable components are represented in the form of chromosomes, initially various chromosomes are randomly generated which are then assessed and selected using fitness value and then crossover and mutation function is performed to obtain a better chromosome. Several iterations are performed till the desired results is achieved. The proposed algorithm is further explained and validated through an illustrative example.

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Efficient optimization of multi-objective redundancy allocation problems in series-parallel systems

Cited by 3 publications

References 24 publications

Determining decoupling points in a supply chain networks using NSGA II algorithm

Determining decoupling points in a supply chain networks using NSGA II algorithm

Efficient optimization of multi-objective redundancy allocation problems in series-parallel systems

Maintenance policy selection of n-component repairable system using Genetic Algorithm

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