A simulated annealing based genetic local search algorithm for multi-objective multicast routing problems

This paper presents a new hybrid evolutionary algorithm to solve multi-objective multicast routing problems in telecommunication networks. The algorithm combines simulated annealing based strategies and a genetic local search, aiming at a more flexible and effective exploration and exploitation in the search space of the complex problem to find more non-dominated solutions in the Pareto Front. Due to the complex structure of the multicast tree, crossover and mutation operators have been specifically devised concerning the features and constraints in the problem. A new adaptive mutation probability based on simulated annealing is proposed in the hybrid algorithm to adaptively adjust the mutation rate according to the fitness of the new solution against the average quality of the current population during the evolution procedure. Two simulated annealing based search direction tuning strategies are applied to improve the efficiency and effectiveness of the hybrid evolutionary algorithm. Simulations have been carried out on some benchmark multi-objective multicast routing instances and a large amount of random networks with five real world objectives including cost, delay, link utilisations, average delay and delay variation in telecommunication networks. Experimental results demonstrate that both the simulated annealing based strategies and the genetic local search within the proposed multi-objective algorithm, compared with other multi-objective evolutionary algorithms, can efficiently identify high quality non-dominated solution set for multi-objective multicast routing problems and outperform other conventional multi-objective evolutionary algorithms in the literature

Solving Many-Objective Car Sequencing Problems on Two-Sided Assembly Lines Using an Adaptive Differential Evolutionary Algorithm

The car sequencing problem (CSP) is addressed in this paper. The original environment of the CSP is modified to reflect real practices in the automotive industry by replacing the use of single-sided straight assembly lines with two-sided assembly lines. As a result, the problem becomes more complex caused by many additional constraints to be considered. Six objectives (i.e. many objectives) are optimised simultaneously including minimising the number of colour changes, minimising utility work, minimising total idle time, minimising the total number of ratio constraint violations and minimising total production rate variation. The algorithm namely adaptive multi-objective evolutionary algorithm based on decomposition hybridised with differential evolution algorithm (AMOEA/D-DE) is developed to tackle this problem. The performances in Pareto sense of AMOEA/D-DE are compared with COIN-E, MODE, MODE/D and MOEA/D. The results indicate that AMOEA/D-DE outperforms the others in terms of convergence-related metrics

Life or cell death: identifying c-Myc regulated genes in two distinct tissues

The c-myc oncogene is over-expressed or deregulated in many human cancers. c-myc encodes a transcription factor, the oncoprotein c-Myc (Myc), which acts as a master regulator of genes involved in such diverse cellular processes as replication and growth, loss of differentiation, invasion, and angiogenesis. Myc can also act as its own tumour suppressor by promoting cell death in the form of apoptosis. Thus, for putative cancer cells to arise, apoptosis must be blocked. Conditional MycERTAM transgenic mice allow regulated activation of Myc in distinct cell populations (skin suprabasal keratinocytes and pancreatic islet β-cells) and have highlighted contrasting behaviour between these two adult tissues in vivo: proliferation in the skin, and apoptosis in the pancreas. Given the crucial dependence on tissue location in vivo, we still do not know enough about the key divergence in Myc-regulated genes and proteins under conditions favouring opposing outcomes. To address this, we performed high-throughput transcriptome analysis using oligonucleotide microarrays. The in vivo transcriptional response to deregulated Myc was analysed for skin keratinocytes and laser-captured pancreatic islets following a time-course of MycERTAM activation. Due to the multi-factorial nature of the experimental design, novel statistical tools were developed allowing the use of linear models for inference of changes in gene-expression based on multiple experimental variables. Comparison of the transcriptional response between the two tissues identified potential signalling pathways which may promote apoptosis of β-cells or survival of skin keratinocytes: the DNA damage response pathway, and the Insulin-like growth factor 1 (Igf1) signalling pathway respectively. In addition, a marked change in expression was detected in members of the steroid hormone-regulated Kallikrein serine protease family in suprabasal keratinocytes but not for β-cells. These have been found to play an important role in regulating Igf1/Igf1-receptor ligation through proteolysis of the Igf1 binding proteins, are previously categorised markers for several human cancers, and may indicate a tissue-specific regulatory mechanism for determining ultimate Myc function in vivo

Evidence for low homology between mammalian leptin and chicken leptin-like gene sequences

Leptin is a 167-amino acid hormone produced chiefly by adipocytes. It plays an important role in regulation of food intake, energy metabolism and reproduction in mammals. However, a leptin gene homologue has yet to be cloned in a non-mammalian vertebrate. The aim of this thesis was to establish the existence of a leptin gene homologue in the domestic chicken (Gallus gallus) genome, and to determine the degree of sequence identity with mammalian leptin genes, and with a putative chicken leptin sequence published during the course of the thesis work. An initial attempt was made to clone the chicken leptin gene by heterologous RT-PCR using degenerate primers to conserved regions of mammalian leptin sequences. However, no leptin-like products were amplified from chicken adipose tissue and liver cDNAs,or from genomic DNA. RTPCR was also used to test the existence of a published chicken leptin cDNA sequence that shares 95% identity with mouse leptin at the nucleotide level. When PCR primers identical to the mouse and published chicken leptin sequences were used, no PCR product sharing close similarity to the mouse leptin sequence were generated from any chicken templates, whereas amplification of mouse leptin leptin sequences was consistently obtained from control mouse templates. Following the failure to clone the chicken leptin by RT-PCR, evidence for the existence of a mammalian-like leptin in the chicken genome was sought by Southern analysis. Southern blots under low stringency hybridization and washing conditions revealed hybridization of a mouse leptin probe to chicken genomic DNA. With high stringency washing, the chicken signal disappeared, while those from sheep and mouse genomic DNA remained. Screening of a chicken adipose tissue cDNA library, and chicken genomic DNA and cosmid libraries with the same mouse probe failed to isolate a chicken leptin homologue. Collectively, these results indicate that if a chicken leptin homologue exists in the chicken genome, it is likely to be of low homology to mammalian leptin sequences. The results do not support the existence of a mouse-like leptin sequence in the chicken genome, an assertion supported by theoretical analysis of the molecular evolution of leptin based on the rate of synonymous substitution. This analysis indicated that the probability that the chicken and mouse leptin sequences are 95% identical, is less than one in a million

GAPS : a hybridised framework applied to vehicle routing problems

In this thesis we consider two combinatorial optimisation problems; the Capacitated Vehicle Routing Problem (CVRP) and the Capacitated Arc Routing Problem (CARP). In the CVRP, the objective is to find a set of routes for a homogenous fleet of vehicles, which must service a set of customers from a central depot. In contrast, the CARP requires a set of routes for a fleet of vehicles to service a set of customers at the street level of an intercity network. After a comprehensive discussion of the existing exact and heuristic algorithmic techniques presented in the literature for these problems, computational experiments to provide a benchmark comparison of a subset of algorithmic implementations for these methods are presented for both the CVRP and CARP, run against a series of dataset instances from the literature. All dataset instances are re-catalogued using a standard format to overcome the difficulties of the different naming schemes and duplication of instances that exist between different sources. We then present a framework, which we shall call Genetic Algorithm with Perturbation Scheme (GAPS), to solve a number of combinatorial optimisation problems. The idea is to use a genetic algorithm as a container framework in conjunction with a perturbation or weight coding scheme. These schemes make alterations to the underlying input data within a problem instance, after which the changed data is fed into a standard problem specific heuristic and the solution obtained decoded to give a true solution cost using the original unaltered instance data. We first present GAPS in a generic context, using the Travelling Salesman Problem (TSP) as an example and then provide details of the specific application of GAPS to both the CVRP and CARP. Computational experiments on a large set of problem instances from the literature are presented and comparisons with the results achieved by the current state of the art algorithmic approaches for both problems are given, highlighting the robustness and effectiveness of the GAPS framework.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Selection of aptamers for human serum albumin and its glycated form

Diabetes prevalence is increasing above and beyond what can be attributed to population growth as reduced physical activity and increased sugar in people's diets is leading to an epidemic that is pushing healthcare systems to breaking point. While therapeutic treatments remain limited for diabetes patients, measurement and management of their glycemic status can prove beneficial. Glucose and HbA1C are currently utilised to manage diabetes in the short and long term respectively. However, problems with the accuracy of the HbA1c in certain diabetes patients, particularly those with renal problems and/or anaemia make it not ideal in all situations. Additionally its half life of 2-3 months make it slow to respond to glycemic changes. Measurement of human serum albumin may be beneficial in both filling the gap between glucose and HbA1c and being less susceptible to interferents. HSA has a half life of between 2-3 weeks and like haemoglobin is readily glycated. Any changes in glycated HSA will demonstrate changes in a patient's glycemic status over the preceding weeks instead of months like HbA1c. Additionally it has been demonstrated to be a better representation of glucose levels in certain patient groups. The relative lack of GHSA testing in the clinic comes down to the cost, complexity and lack of specificity of current techniques. A simple test is needed which can determine the GHSA/HSA ratio of a patient more accurately then current techniques while at a cost that is viable for restrained healthcare budgets. Within this thesis the selection and subsequent testing of aptamers to HSA and early stage glycated HSA (GHSA) is demonstrated.Open Acces

GAPS: a hybridised framework applied to vehicle routing problems

In this thesis we consider two combinatorial optimisation problems; the Capacitated Vehicle Routing Problem (CVRP) and the Capacitated Arc Routing Problem (CARP). In the CVRP, the objective is to find a set of routes for a homogenous fleet of vehicles, which must service a set of customers from a central depot. In contrast, the CARP requires a set of routes for a fleet of vehicles to service a set of customers at the street level of an intercity network. After a comprehensive discussion of the existing exact and heuristic algorithmic techniques presented in the literature for these problems, computational experiments to provide a benchmark comparison of a subset of algorithmic implementations for these methods are presented for both the CVRP and CARP, run against a series of dataset instances from the literature. All dataset instances are re-catalogued using a standard format to overcome the difficulties of the different naming schemes and duplication of instances that exist between different sources. We then present a framework, which we shall call Genetic Algorithm with Perturbation Scheme (GAPS), to solve a number of combinatorial optimisation problems. The idea is to use a genetic algorithm as a container framework in conjunction with a perturbation or weight coding scheme. These schemes make alterations to the underlying input data within a problem instance, after which the changed data is fed into a standard problem specific heuristic and the solution obtained decoded to give a true solution cost using the original unaltered instance data. We first present GAPS in a generic context, using the Travelling Salesman Problem (TSP) as an example and then provide details of the specific application of GAPS to both the CVRP and CARP. Computational experiments on a large set of problem instances from the literature are presented and comparisons with the results achieved by the current state of the art algorithmic approaches for both problems are given, highlighting the robustness and effectiveness of the GAPS framewor