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Differential evolution and large-scale optimization applications
Aleš Zamuda, scientific film, scientific sound or video publication

Abstract: Differential Evolution (DE) is one of the most popular, high-performance optimization algorithms with variants that have been outperforming others for years. As a result, DE has grown to accommodate wide usage for a variety of disciplines across scientific fields. Differential Evolution and Large-Scale Optimization Applications presents a research-based overview and cross-disciplinary applications of optimization algorithms. Emphasizing applications of Differential Evolution (DE) across sectors and laying the foundation for further use of DE algorithms in real-world settings, this video is an essential resource for researchers, engineers, and graduate-level students. Topics Covered : Algorithms, Optimization, Parallel Differential Evolution, Performance Improvement, Stochastic Methods, Tree Model Reconstruction.
Keywords: differential Evolution, optimization, algorithms, stochastic methods, tree models, tree model reconstruction
Published in DKUM: 14.05.2019; Views: 1822; Downloads: 230
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Optimization of a call centre performance using the stochastic queueing models
Alenka Brezavšček, Alenka Baggia, 2014, original scientific article

Abstract: Background: A call centre usually represents the first contact of a customer with a given company. Therefore, the quality of its service is of key importance. An essential factor of the call centre optimization is the determination of the proper number of operators considering the selected performance measure. Results of previous research show that this can be done using the queueing theory approach. Objectives: The paper presents the practical application of the stochastic queueing models aimed at optimizing a Slovenian telecommunication provider’s call centre. Methods/Approach: The arrival and the service patterns were analysed, and it was concluded that the call centre under consideration can be described using the M/M/r {infinity/infinity/FIFO} queueing model. Results: An appropriate number of operators were determined for different peak periods of the working day, taking into consideration the following four performance measures: the expected waiting time, the expected number of waiting customers, the probability that a calling customer will have to wait, and the call centre service level. Conclusions: The obtained results prove the usefulness and applicability of the queueing models as a tool for a call centre performance optimization. In practice, all the data needed for such a mathematical analysis are usually provided. This paper is aimed at illustrating how such data can be efficiently exploited.
Keywords: call centre, service quality, performance measure, optimization, stochastic queueing models
Published in DKUM: 31.03.2017; Views: 1691; Downloads: 405
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Simulation approach to warehouse cost minimization in stochastic environment
Davorin Kofjač, Miroljub Kljajić, 2006, original scientific article

Abstract: Background/Purpose: The objective of inventory management is to balance conflicting goals like keeping stock levels down to have cash available for other purposes and having high stock levels for the continuity of the production. Simulation approach is used to minimize total warehousing cost while no stock-outs occur and warehouse capacity is not exceeded. A case study of replenishment process optimization is presented on several representative materials of an automotive company using two replenishment algorithms: fix review period and full capacity ordering. The presented simulation results indicate considerable cost reduction without violating the mentioned constraints. The fuzzy logic evaluator, a decision support system used for simulation results assessment, is presented and discussed.
Keywords: inventory control, simulation, optimization, stochastic models, fuzzy sets, decision support system
Published in DKUM: 10.07.2015; Views: 1646; Downloads: 45
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