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Article
Publication date: 3 June 2014

Manuel Blanco Abello and Zbigniew Michalewicz

This is the first part of a two-part paper. The purpose of this paper is to report on methods that use the Response Surface Methodology (RSM) to investigate an Evolutionary…

212

Abstract

Purpose

This is the first part of a two-part paper. The purpose of this paper is to report on methods that use the Response Surface Methodology (RSM) to investigate an Evolutionary Algorithm (EA) and memory-based approach referred to as McBAR – the Mapping of Task IDs for Centroid-Based Adaptation with Random Immigrants. Some of the methods are useful for investigating the performance (solution-search abilities) of techniques (comprised of McBAR and other selected EA-based techniques) for solving some multi-objective dynamic resource-constrained project scheduling problems with time-varying number of tasks.

Design/methodology/approach

The RSM is applied to: determine some EA parameters of the techniques, develop models of the performance of each technique, legitimize some algorithmic components of McBAR, manifest the relative performance of McBAR over the other techniques and determine the resiliency of McBAR against changes in the environment.

Findings

The results of applying the methods are explored in the second part of this work.

Originality/value

The models are composite and characterize an EA memory-based technique. Further, the resiliency of techniques is determined by applying Lagrange optimization that involves the models.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 7 no. 2
Type: Research Article
ISSN: 1756-378X

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Article
Publication date: 23 August 2011

Neal Wagner, Zbigniew Michalewicz, Sven Schellenberg, Constantin Chiriac and Arvind Mohais

The purpose of this paper is to describe a real‐world system developed for a large food distribution company which requires forecasting demand for thousands of products across…

3730

Abstract

Purpose

The purpose of this paper is to describe a real‐world system developed for a large food distribution company which requires forecasting demand for thousands of products across multiple warehouses. The number of different time series that the system must model and predict is on the order of 105. The study details the system's forecasting algorithm which efficiently handles several difficult requirements including the prediction of multiple time series, the need for a continuously self‐updating model, and the desire to automatically identify and analyze various time series characteristics such as seasonal spikes and unprecedented events.

Design/methodology/approach

The forecasting algorithm makes use of a hybrid model consisting of both statistical and heuristic techniques to fulfill these requirements and to satisfy a variety of business constraints/rules related to over‐ and under‐stocking.

Findings

The robustness of the system has been proven by its heavy and sustained use since being adopted in November 2009 by a company that serves 91 percent of the combined populations of Australia and New Zealand.

Originality/value

This paper provides a case study of a real‐world system that employs a novel hybrid model to forecast multiple time series in a non‐static environment. The value of the model lies in its ability to accurately capture and forecast a very large and constantly changing portfolio of time series efficiently and without human intervention.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 4 no. 3
Type: Research Article
ISSN: 1756-378X

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Article
Publication date: 3 June 2014

Manuel Blanco Abello and Zbigniew Michalewicz

This is the second part of a two-part paper. The purpose of this paper is to report the results on the application of the methods that use the Response Surface Methodology to…

94

Abstract

Purpose

This is the second part of a two-part paper. The purpose of this paper is to report the results on the application of the methods that use the Response Surface Methodology to investigate an evolutionary algorithm (EA) and memory-based approach referred to as McBAR – the Mapping of Task IDs for Centroid-Based Adaptation with Random Immigrants.

Design/methodology/approach

The methods applied in this paper are fully explained in the first part. They are utilized to investigate the performances (ability to determine solutions to problems) of techniques composed of McBAR and some EA-based techniques for solving some multi-objective dynamic resource-constrained project scheduling problems with a variable number of tasks.

Findings

The main results include the following: first, some algorithmic components of McBAR are legitimate; second, the performance of McBAR is generally superior to those of the other techniques after increase in the number of tasks in each of the above-mentioned problems; and third, McBAR has the most resilient performance among the techniques against changes in the environment that set the problems.

Originality/value

This paper is novel for investigating the enumerated results.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 7 no. 2
Type: Research Article
ISSN: 1756-378X

Keywords

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Article
Publication date: 23 November 2012

Maksud Ibrahimov, Arvind Mohais, Sven Schellenberg and Zbigniew Michalewicz

The purpose of this paper and its companion (Part I: single and two‐component supply chains) is to investigate methods to tackle complexities, constraints (including time‐varying…

1240

Abstract

Purpose

The purpose of this paper and its companion (Part I: single and two‐component supply chains) is to investigate methods to tackle complexities, constraints (including time‐varying constraints) and other challenges. In this part, attention is devoted to multi‐silo supply chain and the relationships between the components. The first part of the paper aims to consider two types of experimental supply chains: with one‐to‐many and many‐to‐one relationships. The second half of the paper aims to present two approaches on optimising the material flow in the real‐world supply chain network.

Design/methodology/approach

Cooperative coevolutionary and classical sequential approaches are taken to address the experimental multi‐silo supply chains. Due to the nature and the complexity of the supply chain presented in the second half of the paper, evolutionary algorithm was not sufficient to tackle the problem. A fuzzy‐evolutionary algorithm is proposed to address the problem.

Findings

The proposed systems produce solutions better than solutions proposed by human experts and in much shorter time.

Originality/value

The paper discusses various algorithms to provide the decision support for the real‐world problems. The system proposed for the real‐world supply chain is in the process of integration to the production environment.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 5 no. 4
Type: Research Article
ISSN: 1756-378X

Keywords

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Article
Publication date: 23 November 2012

Maksud Ibrahimov, Arvind Mohais, Sven Schellenberg and Zbigniew Michalewicz

The purpose of this paper and its companion (Part II: multi‐silo supply chains) is to investigate methods to tackle complexities, constraints (including time‐varying constraints…

835

Abstract

Purpose

The purpose of this paper and its companion (Part II: multi‐silo supply chains) is to investigate methods to tackle complexities, constraints (including time‐varying constraints) and other challenges. In tis part, the paper aims to devote attention to single silo and two‐silo supply chains. It also aims to discuss three models. The first model is based on the winebottling real‐world system and exposes complexities of a single operational component of the supply chain. The second model extends it to two components: production and distribution. The last system is a real‐world implementation of the two‐component supply chain.

Design/methodology/approach

Evolutionary approach is proposed for a single component problem. The two‐component experimental supply chain is addressed by the algorithm based on cooperative coevolution. The final problem of steel sheet production is tackled with the evolutionary algorithm.

Findings

The proposed systems produce solutions better than solutions proposed by human experts and in a much shorter time.

Originality/value

The paper discusses various algorithms to provide the decision support for the real‐world problems. The proposed systems are in the production use.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 5 no. 4
Type: Research Article
ISSN: 1756-378X

Keywords

Available. Content available
Article
Publication date: 20 February 2007

972

Abstract

Details

Kybernetes, vol. 36 no. 1
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 1 August 2002

Laura Núñez‐Letamendia

Outlines the development of genetic algorithms (GA), explains how they generate solutions to problems and applies four GA models incorporating different factors (e.g. risk…

520

Abstract

Outlines the development of genetic algorithms (GA), explains how they generate solutions to problems and applies four GA models incorporating different factors (e.g. risk, transaction costs etc.) to financial investment strategies. Uses 1987‐1996 share price data from the Madrid Stock Exchange (Spain) and a buy‐and‐hold strategy in the IBEX‐35 index as a benchmark. Shows that all four GA models generat superior daily returns of long positions with lower risk; and discusses the variations between them in detail.

Details

Managerial Finance, vol. 28 no. 8
Type: Research Article
ISSN: 0307-4358

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