Condition-based maintenance optimization by means of genetic algorithms and Monte Carlo simulation

Marseguerra, M.; Zio, Enrico; Podofillini, Luca

doi:10.1016/s0951-8320(02)00043-1

Cited by 305 publications

(165 citation statements)

References 19 publications

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“…A mating pool of size N is created by selecting individuals with higher fitness scores. This created population is allowed to evolve in successive generations through the following steps (Marseguerra et al, 2002): 1. Selection of a pair of individuals as parents; 2.…”

Section: Alphanumeric Journalmentioning

confidence: 99%

Comparison Of Periodic-Review Inventory Control Policies In A Serial Supply Chain

Kabadayı¹,

Keskintürk²

2015

Alphanumeric

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Supply chain management provides customers with the right product or service at a reasonable price, in the right place, at the right time, and with the best quality possible, thus increasing customer satisfaction. The inventory is held at the multiple sites in a supply chain. Effective and efficient management of inventory in the supply chain process has a significant impact on improving the ultimate customer service provided to the customer. Reducing inventory cost, which is a major part of total supply chain costs, will help provide products or services at a better price. This study aims to compare (R, S) and (R, S, Qmin) inventory control policies in a serial supply chain. We develop a simulation based genetic algorithm (GA) in order to find the optimal numerical "S" value that minimizes the total supply chain cost (TSCC) and compare our results between two methods.

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Section: Alphanumeric Journalmentioning

confidence: 99%

Comparison Of Periodic-Review Inventory Control Policies In A Serial Supply Chain

Kabadayı¹,

Keskintürk²

2015

Alphanumeric

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“…For systems with many components subject to soft failures, Zhu et al [38] proposed a model with a control limit policy per component and a the joint maintenance interval of the system (in this system all maintenance actions are executed at the scheduled downs). Moreover, for larger scale problems, there is research based on Monte Carlo simulation and genetic algorithms; see Marseguerra et al [21] and Barata et al [2]. Alternatively, Tian et al [28] proposed two maintenance policies for multi-component systems using the proportional hazard model, and Tian and…”

Section: Introductionmentioning

confidence: 99%

A condition-based maintenance model for a single component in a system with scheduled and unscheduled downs

Zhu

Peng

Timmermans³

et al. 2017

International Journal of Production Economics

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“…In light of the above considerations, many scholars have conducted further research on DER system optimization with regard uncertainty. With regard to stochastic uncertain optimization, the Monte Carlo simulation is one of the most common methods to deal with models [45][46][47]. The principle is that the uncertain parameters of the models are stochastically generated with several groups of values according to probability distributions.…”

Section: Introductionmentioning

confidence: 99%

An MILP Method for Design of Distributed Energy Resource System Considering Stochastic Energy Supply and Demand

Duan

Yan

et al. 2017

Energies

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A distributed energy resource (DER) system, which can be defined as a medium or small energy conversion and utilization system with various functions for meeting multiple targets, is directly oriented towards users and achieves on-site production and energy supply according to users' demands. Optimization research on system construction has recently become an important issue. In this paper, simple stochastic mathematical equations were used to interpret the optimal design problem of a DER system, and based on this, a novel method for solving the optimization problem, which has multi-dimensional stochastic uncertainties (involving the price of input-energy and energy supply and demand), was put forward. A mixed-integer linear programming (MILP) model was established for the optimal design of the DER system by combining the ideas of mean value and variance, aiming to minimize the total costs, including facility costs, energy purchase costs, and loss caused by energy supply shortage, and considering the energy balance and facility performance constraints. In the end, a DER system design for an office building district in Xuzhou, China, was taken as an example to verify the model. The influences of uncertainty on the selection of system facilities and the economic evaluation were analyzed. The result indicated that uncertainty of energy demand played a significant role in optimal design, whereas energy price played a negligible role. With respect to economy, if uncertainties are not considered in system design, it will result in a short supply, and therefore the total cost will increase considerably. The calculation convergence was compared with previous work. The implementation results showed the practicality and efficiency of the proposed method.

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Condition-based maintenance optimization by means of genetic algorithms and Monte Carlo simulation

Cited by 305 publications

References 19 publications

Comparison Of Periodic-Review Inventory Control Policies In A Serial Supply Chain

Comparison Of Periodic-Review Inventory Control Policies In A Serial Supply Chain

A condition-based maintenance model for a single component in a system with scheduled and unscheduled downs

An MILP Method for Design of Distributed Energy Resource System Considering Stochastic Energy Supply and Demand

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