An integrated scheduling problem of PCB components on sequential pick-and-place machines:mathematical models and heuristic solutions

This paper formulates several mathematical models for determining the optimal sequence of component placements and assignment of component types to feeders simultaneously or the integrated scheduling problem for a type of surface mount technology placement machines, called the sequential pick-andplace (PAP) machine. A PAP machine has multiple stationary feeders storing components, a stationary working table holding a printed circuit board (PCB), and a movable placement head to pick up components from feeders and place them to a board. The objective of integrated problem is to minimize the total distance traveled by the placement head. Two integer nonlinear programming models are formulated first. Then, each of them is equivalently converted into an integer linear type. The models for the integrated problem are verified by two commercial packages. In addition, a hybrid genetic algorithm previously developed by the authors is adopted to solve the models. The algorithm not only generates the optimal solutions quickly for small-sized problems, but also outperforms the genetic algorithms developed by other researchers in terms of total traveling distance.

Integrated component scheduling models for chip shooter machines

This paper focuses on minimizing printed circuit board (PCB) assembly time for a chipshootermachine, which has a movable feeder carrier holding components, a movable X–Y table carrying a PCB, and a rotary turret with multiple assembly heads. The assembly time of the machine depends on two inter-related optimization problems: the component sequencing problem and the feeder arrangement problem. Nevertheless, they were often regarded as two individual problems and solved separately. This paper proposes two complete mathematical models for the integrated problem of the machine. The models are verified by two commercial packages. Finally, a hybrid genetic algorithm previously developed by the authors is presented to solve the model. The algorithm not only generates the optimal solutions quickly for small-sized problems, but also outperforms the genetic algorithms developed by other researchers in terms of total assembly time.

PCB assembly line assignment:a genetic algorithm approach

Purpose – This paper sets out to study a production-planning problem for printed circuit board (PCB) assembly. A PCB assembly company may have a number of assembly lines for production of several product types in large volume. Design/methodology/approach – Pure integer linear programming models are formulated for assigning the product types to assembly lines, which is the line assignment problem, with the objective of minimizing the total production cost. In this approach, unrealistic assignment, which was suffered by previous researchers, is avoided by incorporating several constraints into the model. In this paper, a genetic algorithm is developed to solve the line assignment problem. Findings – The procedure of the genetic algorithm to the problem and a numerical example for illustrating the models are provided. It is also proved that the algorithm is effective and efficient in dealing with the problem. Originality/value – This paper studies the line assignment problem arising in a PCB manufacturing company in which the production volume is high.

Evolutionary neural networks : models and applications

The scaling problems which afflict attempts to optimise neural networks (NNs) with genetic algorithms (GAs) are disclosed. A novel GA-NN hybrid is introduced, based on the bumptree, a little-used connectionist model. As well as being computationally efficient, the bumptree is shown to be more amenable to genetic coding lthan other NN models. A hierarchical genetic coding scheme is developed for the bumptree and shown to have low redundancy, as well as being complete and closed with respect to the search space. When applied to optimising bumptree architectures for classification problems the GA discovers bumptrees which significantly out-perform those constructed using a standard algorithm. The fields of artificial life, control and robotics are identified as likely application areas for the evolutionary optimisation of NNs. An artificial life case-study is presented and discussed. Experiments are reported which show that the GA-bumptree is able to learn simulated pole balancing and car parking tasks using only limited environmental feedback. A simple modification of the fitness function allows the GA-bumptree to learn mappings which are multi-modal, such as robot arm inverse kinematics. The dynamics of the 'geographic speciation' selection model used by the GA-bumptree are investigated empirically and the convergence profile is introduced as an analytical tool. The relationships between the rate of genetic convergence and the phenomena of speciation, genetic drift and punctuated equilibrium arc discussed. The importance of genetic linkage to GA design is discussed and two new recombination operators arc introduced. The first, linkage mapped crossover (LMX) is shown to be a generalisation of existing crossover operators. LMX provides a new framework for incorporating prior knowledge into GAs.Its adaptive form, ALMX, is shown to be able to infer linkage relationships automatically during genetic search.

Genetic and environmentally derived variation in the cell wall composition of miscanthus and implications for thermo-chemical conversion

Fifteen Miscanthus genotypes grown in five locations across Europe were analysed to investigate the influence of genetic and environmental factors on cell wall composition. Chemometric techniques combining near infrared reflectance spectroscopy and conventional chemical analyses were used to construct calibration models for determination of acid detergent lignin, acid detergent fibre, and neutral detergent fibre from sample spectra. The developed equations were shown to predict cell wall components with a good degree of accuracy and significant genetic and environmental variation was identified. The influence of nitrogen and potassium fertiliser on the dry matter yield and cell wall composition of M. x giganteus was investigated. A detrimental affect on feedstock quality was observed to result from application of these inputs which resulted in an overall reduction in concentrations of cell wall components and increased accumulation of ash within the biomass. Pyrolysis-gas chromatography-mass spectrometry and thermo-gravimetric analysis indicates that genotypes other than the commercially cultivated M. x giganteus have potential for use in energy conversion processes and in the bio-refining. The yields and quality parameters of the pyrolysis liquids produced from Miscanthus compared favourably with that produced from SRC willow and produced a more stable pyrolysis liquid with a higher lower heating value. Overall, genotype had a more significant effect on cell wall composition than environment. This indicates good potential for dissection of this trait by QTL analysis and also for plant breeding to produce new genotypes with improved feedstock characteristics for energy conversion.

Genetic risk factors and age-related macular degeneration (AMD)

Age related macular degeneration (AMD) is the leading cause of blindness in individuals older than 65 years of age. It is a multifactorial disorder and identification of risk factors enables individuals to make lifestyle choices that may reduce the risk of disease. Collaboration between geneticists, ophthalmologists, and optometrists suggests that genetic risk factors play a more significant role in AMD than previously thought. The most important genes are associated with immune system modulation and the complement system, e.g., complement factor H (CFH), factor B (CFB), factor C3, and serpin peptidase inhibitor (SERPING1). Genes associated with membrane transport, e.g., ATP-binding cassette protein (ABCR) and voltage-dependent calcium channel gamma 3 (CACNG3), the vascular system, e.g., fibroblast growth factor 2 (FGF2), fibulin-5, lysyl oxidase-like gene (LOXL1) and selectin-P (SELP), and with lipid metabolism, e.g., apolipoprotein E (APOE) and hepatic lipase (LIPC) have also been implicated. In addition, several other genes exhibit some statistical association with AMD, e.g., age-related maculopathy susceptibility protein 2 (ARMS2) and DNA excision repair protein gene (ERCC6) but more research is needed to establish their significance. Modifiable risk factors for AMD should be discussed with patients whose lifestyle and/or family history place them in an increased risk category. Furthermore, calculation of AMD risk using current models should be recommended as a tool for patient education. It is likely that AMD management in future will be increasingly influenced by assessment of genetic risk as such screening methods become more widely available. © 2013 Spanish General Council of Optometry.