Demonstrating the importance of using total time balance instead of route balance on a multi-objective vehicle routing problem with time windows

‘Route balance’ is the difference between the longest and the shortest among all the route lengths. The route balance is frequently considered in a vehicle routing problem (VRP) for balancing the distance travelled among delivery vehicles. This is a common practice since in VRPs there are no time elements. However, in recent years, some research works have considered route balance in a vehicle routing problem with time windows (VRPTW). As there are more time elements in VRPTW, this paper refutes that route balance is sufficient for VRPTW by simultaneously optimising makespan and workload imbalance using ‘total time balance’ instead of route balance. On the other hand, ‘total time balance’ is the difference between the longest total time taken and the shortest total time taken among delivery vehicles. As such, makespan is the longest total time taken among vehicles. Total time taken for a vehicle is the sum of vehicle run time, waiting time and service time. In order to demonstrate the importance of using total time balance instead of route balance on VRPTW, three different multi-objective VRPTW models, namely, (1) only with general VRPTW objectives (i.e. ‘total distance travelled’ by all vehicles and ‘total number of vehicles’ used), (2) general VRPTW objectives with route balance and (3) general VRPTW objectives with total time balance are developed and solved by fitness aggregated genetic algorithm (FAGA) for 36 Solomon’s benchmark instances. By comparison of the makespan produced by the FAGA between the three cases, the importance of using total time balance instead of route balance on multi-objective VRPTW is demonstrated. Also, the makespan produced by the FAGA for the third case, i.e. general VRPTW objectives with total time balance is compared with the makespan produced by fitness aggregated differential evolution (FADE). By comparing makespan with statistical testing between FAGA and FADE, the outperformance of FAGA over FADE is verified. To check the practicality of the total time balance on multi-objective VRPTW, an instance with real time windows is also solved for the three cases by the FAGA and its makespan are compared and reported.     

A Novel Fatty Acyl Desaturase from the Pheromone Glands of Ctenopseustis obliquana and C. herana with Specific Z5-Desaturase Activity on Myristic Acid

Sexual communication in the Lepidoptera typically involves a female-produced sex pheromone that attracts males of the same species. The most common type of moth sex pheromone comprises individual or blends of fatty acyl derivatives that are synthesized by a specific enzymatic pathway in the female’s pheromone gland, often including a desaturation step. This reaction is catalyzed by fatty acyl desaturases that introduce double bonds at specific locations in the fatty acid precursor backbone. The two tortricid moths, Ctenopseustis obliquana and C. herana (brown-headed leafrollers), which are endemic in New Zealand, both use (Z)-5-tetradecenyl acetate as part of their sex pheromone. In C. herana, (Z)-5-tetradecenyl acetate is the sole component of the pheromone. Labeling experiments have revealed that this compound is produced via an unusual Δ5-desaturation of myristic acid. Previously six desaturases were identified from the pheromone glands of Ctenopseustis and its sibling genus Planotortrix, with one differentially regulated to produce the distinct blends used by individual species. However, none were able to conduct the Δ5-desaturation observed in C. herana, and presumably C. obliquana. We have now identified an additional desaturase gene, desat7, expressed in the pheromone glands of both Ctenopseustis species, which is not closely related to any previously described moth pheromone desaturase. The encoded enzyme displays Δ5-desaturase activity on myristic acid when heterologously expressed in yeast, but is not able to desaturate any other fatty acid (C8–C16). We conclude that desat7 represents a new group of desaturases that has evolved a role in the biosynthesis of sex pheromones in moths.     

Effect of Deposition Potential on Synthesis,Structural,Morphological and Photoconductivity Response of Cu_2O Thin Films by Electrodeposition Technique

The present work describes the effect of deposition potentials on structural, morphological, optical, electrical and photoconductivity responses of cuprous oxide(Cu_2O) thin films deposited on fluorine-doped tin oxide glass substrate by employing electrodeposition technique. X-ray diffraction patterns reveal that the deposited films have a cubic structure grown along the preferential(111) growth orientation and crystallinity of the film deposited at. 0.4 V is improved compared to the films deposited at. 0.2,. 0.3 and. 0.5 V. Scanning electron microscopy displays that surface morphology of Cu_2O film has a well-defined three-sided pyramid-shaped grains which are uniformly distributed over the surface of the substrates and are significantly changed as a function of deposition potential. Raman and photoluminescence spectra manifest that the film deposited at. 0.4 V has a good crystal quality with higher acceptor concentration compared to other films. UV–visible analysis illustrates that the absorption of Cu_2O thin film deposited at. 0.4 V is notably higher compared to other films and the band gap of Cu_2O thin films decreases from 2.1 to 2.04 eV with an increase in deposition potential from. 0.2 to. 0.5 V.The frequency–temperature dependence of impedance analysis shows that the film deposited at. 0.4 V has a high conductivity.I – V measurements elucidate that the film deposited at. 0.4 V exhibits a good photoconductivity response compared to films deposited in other deposition potentials.     

A comprehensive process of reverse engineering from 3D meshes to CAD models

In an industrial context, most manufactured objects are designed using CAD (Computer-Aided Design) software. For visualization, data exchange or manufacturing applications, the geometric model has to be discretized into a 3D mesh composed of a finite number of vertices and edges. However, the initial model may sometimes be lost or unavailable. In other cases, the 3D discrete representation may be modified, e.g. after numerical simulation, and no longer corresponds to the initial model. A retro-engineering method is then required to reconstruct a 3D continuous representation from the discrete one.In this paper, we present an automatic and comprehensive retro-engineering process dedicated mainly to 3D meshes obtained initially by mechanical object discretization. First, several improvements in automatic detection of geometric primitives from a 3D mesh are presented. Then a new formalism is introduced to define the topology of the object and compute the intersections between primitives. The proposed method is validated on 3D industrial meshes.     

Improvements in the accuracy of an Inverse Problem Engine's output for the prediction of below-knee prosthetic socket interfacial loads

The monitoring of in-service loads on many components has become a routine operation for simple and well-understood cases in engineering. However, as the complexity of the structure increases so does the difficulty in obtaining an acceptable understanding of the real loading. It has been shown that it is possible to solve these problems by interfacing traditional analysis methodologies with more modern mathematical methods (i.e. artificial intelligence) in order to create a hybrid analysis tool. It has, however, been recognised that an Artificial Neural Network (ANN) predicts poorly in the high and low ranges of the envelope of which it is trying to predict. This paper presents results of research to develop the ANN Difference Method to improve the accuracy of the Inverse Problem Engine's output. This method has been applied to accurately predict the complex pressure distribution at the residual limb/socket interface of a lower-limb prosthesis. It has been shown that application of the ANN Difference Method to the output of a backpropagation neural network can reduce inherent errors that exist at the low and high ends of the ANN solution envelope. This powerful approach can offer load information at high speed once the relationship between the loading and response of the component has been established through training the ANN. Utilising an experimental technique combined with an ANN can provide in-service loads on complex components in real time as part of a sophisticated embedded system.     

Surrogate assisted‐hybrid differential evolution algorithm using diversity control

Evolutionary algorithms (EAs) being a major optimization framework, typically require a considerable number of function evaluations to locate an optimal solution for computationally intensive real‐world optimization problems. In order to solve complex multimodal problems within a limited computational budget, surrogate models are integrated with EA. The overall performance of such algorithms not only depends on the construction and integration procedure of the model, but also on the efficiency of the underlying EA in overcoming premature convergence. This can be achieved through diversity control and parameter adaptation methodology in EAs. In this paper, an improved algorithm, namely Diversity Controlled Parameter adapted Differential Evolution with Local Search (DCPaDE‐LS) is integrated into two dynamic surrogate models and two variants, namely Surrogate Assisted Parameter adapted Differential Evolution with Artificial Neural Networks and Response Surface Methodology (SAPDE‐ANN and SAPDE‐RSM) are proposed. They reduce the exact function evaluations for complex, multimodal problems. The performance of the proposed variants are compared on a set of 26 bound‐constrained benchmark functions scalable with 10 and 30 dimensions, with respect to average number of function evaluations (NFE), success rate (SR) and % reduction in NFE in 30 independent trials. The SAPDE variants are compared with Self‐adaptive Differential Evolution, DCPaDE‐LS, Increasing Population Size Covariance Matrix Adaptation Evolution Strategy and Comprehensive Learning Particle Swarm Optimization. The SAPDE variants are able to reduce the NFE without loss in SR for all the functions. The algorithms are also validated using 12 solvable functions from CEC 2005. Of the two variants, SAPDE‐ANN reports reduced NFE in more functions compared with SAPDE‐RSM. Results reveal that the proposed SAPDE algorithm can be applied to real‐world optimization problems.     

Influence of Filler Precoating and Printing Parameter on Mechanical Properties of 3D Printed Acrylonitrile Butadiene Styrene/Zinc Oxide Composite

Acrylonitrile butadiene styrene (ABS)/zinc oxide(ZnO) composites have been fabricated via fused deposition modelling technique. The effect of filler precoating and printing parameters on mechanical properties of the composites are investigated. The incorporation of precoated fillers and increase of infill density improve the tensile strength, Young’s modulus and hardness of the composites. Printing pattern determines mainly the tensile properties of the composites but has no significant effect on the hardness. Based on experimental results, it is suggested that line pattern printed with precoated fillers at medium dispenser speed and 100% infill density has resulted improved mechanical properties.