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Contribution Overview to the Evaluation and Development of Spare Parts Management Models: Meta-Heuristic and Probabilistic Methods

Bounou Oumaima, El Barkany Abdellah, El Biyaali Ahmed

Management and Production Engineering Review

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2021

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Vol. 12, No. 1

24--37

EN

The presence of the spare parts stock is a necessity to ensure the continuity of services. The supply of spare parts is a special case of the global supply chain. The main objective of our research is to propose a global spare parts management approach which allows decision makers to determine the essential points in stock management. Thus, it is important for the stock manager to evaluate the system considered from time to time based on performance indicators. Some of these indicators are presented in the form of a dashboard. The presentation of this chapter chronologically traces the progress of our research work. In the first part, we present the work related to the forecast of spare parts needs through parametric and statistical methods as well as a Bayesian modelling of demand forecasting. To measure the appreciation of the supply of spare parts inventory, the second part focuses on work related to the evaluation of the performance of the spare parts system. Thus, we concretize the link between the management of spare parts and maintenance in the third part, more precisely, in the performance evaluation of the joint -management of spare parts and maintenance, in order to visualize the influence of parameters on the system. In the last section of this chapter, we will present the metaheuristic methods and their use in the management of spare parts and maintenance and make an analysis on work done in the literature.

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Metaheuristic optimization of marginal risk constrained long - short portfolios

Vijayalakshmi Pai G. A., Michel T.

Journal of Artificial Intelligence and Soft Computing Research

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2012

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Vol. 2, No. 3

259--274

EN

The problem of portfolio optimization with its twin objectives of maximizing expected portfolio return and minimizing portfolio risk renders itself difficult for direct solving using traditional methods when constraints reflective of investor preferences, risk management and market conditions are imposed on the underlying mathematical model. Marginal risk that represents the risk contributed by an asset to the total portfolio risk is an important criterion during portfolio selection and risk management. However, the inclusion of the constraint turns the problem model into a notorious non-convex quadratic constrained quadratic programming problem that seeks acceptable solutions using metaheuristic methods. In this work, two metaheuristic methods, viz., Evolution Strategy with Hall of Fame and Differential Evolution (rand/1/bin) with Hall of Fame have been evolved to solve the complex problem and compare the quality of the solutions obtained. The experimental studies have been undertaken on the Bombay Stock Exchange (BSE200) data set for the period March 1999-March 2009. The efficiency of the portfolios obtained by the two metaheuristic methods have been analyzed using Data Envelopment Analysis.

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Structure optimization of power system using Simulated Annealing Algorithm

Rami A.

Przegląd Elektrotechniczny

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2011

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R. 87, nr 1

258-261

EN

The simulated annealing algorithm is used as an optimization technique to solve the problem of total investment cost optimization, subject to the reliability constraints. The problem of optimization of the structure of a power system where redundant elements are included in order to provide a desired level of reliability is known as Redundancy Optimization Problem. The problem is presented by multi-state series-parallel systems. System reliability is defined as the ability to satisfy consumer demand which is represented as a piecewise cumulative load curve. We supposed variation of the load cumulative demand curve null. A universal generating function technique is applied to evaluate system availability.

PL

Algorytm symulowanego wyżarzania jest używany jako technika optymalizacji do rozwiązywania problemów optymalizacji kosztów przy wymuszonej niezawodności. Problem optymalizacji struktury systemu mocy z nadmiarowym elementem zabezpieczającym pożądaną niezawodność jest znany jako Redendancy Optimization Problem. Problem jest analizowany w systemie szeregowo-równoległym. Niezawodność systemu jest zdefiniowana jako zdolność spełnienia żądań konsumentów, które są reprezentowane jako część skumulowanej krzywej obciążeń. Założono zerową wariację krzywej obciążeń. Zaproponowano uniwersalną technikę możliwą do zastosowania w celu oceny zdolności systemu.