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Chapter and Conference Paper
Comparing ML Models for Food Production Forecasting
Food production forecasting is a challenge to decision-makers at agriculture authorities. In this study, we compare the performance of three different Machine Learning (ML) approaches for predicting the produc...
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Chapter and Conference Paper
Modified RK-EDA to Solve a Permutation-Based Spare Part Allocation Problem
This paper presents an application of evolutionary algorithms for a spares part allocation problem in the telecom industry. The aim is to have the right spare parts at the right time at the right place in orde...
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Chapter and Conference Paper
On Predicting the Work Load for Service Contractors
Service Industries rely on resource planning and service optimisation to improve operational efficiency. Forecasting the demand for the service with high accuracy plays a significant role in proactively planni...
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Chapter and Conference Paper
Evolving Large Scale Prediction Models for Vehicle Volume Forecasting in Service Stations
Resource Planning and Service Optimization for operational efficiency constitutes a major factor in the service industry. Internally most of it is dependent on the accuracy of the forecasted demand for the ser...
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Article
Novel secure surgical telepresence using enhanced advanced encryption standard: during, pre and post surgery
Security during surgical telepresence has not yet been sufficiently considered. This paper aims to propose a solution to enhance security during surgery between the site of surgery (local site) and the site th...
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Chapter and Conference Paper
An Application of EDA and GA for Permutation Based Spare Part Allocation Problem
Enterprise Resource management is crucial to the success of any service organizations. Having right resource at the right time at the right place can make a big difference to the quality of their service offe...
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Chapter and Conference Paper
Evolving Prediction Models with Genetic Algorithm to Forecast Vehicle Volume in a Service Station (Best Application Paper)
In the service industry, having an efficient resource plan is of utmost importance for operational efficiency. An accurate forecast of demand is crucial in obtaining a resource plan which is efficient. In thi...
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Chapter and Conference Paper
A Multi-objective Design of In-Building Distributed Antenna System Using Evolutionary Algorithms
The increasing data traffic inside buildings requires maintaining good cellular network coverage for indoor mobile users. Passive In-building Distributed Antenna System (IB-DAS) is one of the most efficient me...
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Chapter and Conference Paper
Predicting Fluid Work Demand in Service Organizations Using AI Techniques
Prediction is about making claims on future events based on past information and the current state. Predicting workforce demand for the future can help service organizations adjust their resources and reach t...
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Chapter
Understanding Team Dynamics with Agent-Based Simulation
Agent-based simulation is increasingly used in industry to model systems of interest allowing the evaluation of alternative scenarios. By this means, business managers can estimate the consequences of policy c...
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Article
A Markovianity based optimisation algorithm
Several Estimation of Distribution Algorithms (EDAs) based on Markov networks have been recently proposed. The key idea behind these EDAs was to factorise the joint probability distribution of solution variabl...
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Book
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Chapter
Applications of Distribution Estimation Using Markov Network Modelling (DEUM)
In recent years, Markov Network EDAs have begun to find application to a range of important scientific and industrial problems. In this chapter we focus on several applications of Markov Network EDAs classifie...
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Chapter
A Review of Estimation of Distribution Algorithms and Markov Networks
This chapter reviews some of the popular EDAs based on Markov Networks. It starts by giving introduction to general EDAs and describes the motivation behind their emergence. It then categorises EDAs according ...
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Chapter
DEUM - Distribution Estimation Using Markov Networks
DEUM is one of the early EDAs to use Markov Networks as its model of probability distribution. It uses undirected graph to represent variable interaction in the solution, and builds a model of fitness function...
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Chapter
Probabilistic Graphical Models and Markov Networks
This chapter introduces probabilistic graphical models and explain their use for modelling probabilistic relationships between variables in the context of optimisation with EDAs.We focus on Markov networksmode...
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Chapter
MOA - Markovian Optimisation Algorithm
In this chapter we describe Markovian Optimisation Algorithm (MOA), one of the recent developments in MN based EDA. It uses the local Markov property to model the dependency and directly sample from it without...
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Chapter and Conference Paper
Intelligent Tuning of a Dynamic Business Simulation Environment
One important use of simulation tools is to use an existing base-model of a business, representing the systems of interest, and then modelling and testing alternative scenarios by making changes to this base-m...
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Chapter
DEUM – A Fully Multivariate EDA Based on Markov Networks
Recent years have seen an increasing interest in Markov networks as an alternative approach to probabilistic modelling in estimation of distribution algorithms (EDAs). Distribution Estimation Using Markov netw...
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Chapter and Conference Paper
Analysing the Effect of Demand Uncertainty in Dynamic Pricing with EAs
Dynamic pricing is a pricing strategy where a firm adjust the price for their products and services as a function of its perceived demand at different times. In this paper, we show how Evolutionary algorithms ...
