A hybrid genetic algorithm for sequencing PCB component placement

A chip shooter machine for electronic components assembly has a movable feeder carrier holding components, a movable X-Y table carrying a printed circuit board (PCB), and a rotary turret having multiple assembly heads. This paper presents a hybrid genetic algorithm to optimize the sequence of component placements for a chip shooter machine. The objective of the problem is to minimize the total traveling distance of the X-Y table or the board. The genetic algorithm developed in the paper hybridizes the nearest neighbor heuristic, and an iterated swap procedure, which is a new improved heuristic. We have compared the performance of the hybrid genetic algorithm with that of the approach proposed by other researchers and have demonstrated our algorithm is superior in terms of the distance traveled by the X-Y table or the board.

A hybrid genetic algorithm for component sequencing and feeder arrangement

This paper presents a hybrid genetic algorithm to optimize the sequence of component placements on a printed circuit board and the arrangement of component types to feeders simultaneously for a pick-and-place machine with multiple stationary feeders, a fixed board table and a movable placement head. The objective of the problem is to minimize the total travelling distance, or the travelling time, of the placement head. The genetic algorithm developed in the paper hybrisizes different search heuristics including the nearest neighbor heuristic, the 2-opt heuristic, and an iterated swap procedure, which is a new improving heuristic. Compared with the results obtained by other researchers, the performance of the hybrid genetic algorithm is superior to others in terms of the distance travelled by the placement head.

Discovery of active proteins directly from combinatorial randomized protein libraries without display, purification or sequencing:identification of novel zinc finger proteins.

We have successfully linked protein library screening directly with the identification of active proteins, without the need for individual purification, display technologies or physical linkage between the protein and its encoding sequence. By using 'MAX' randomization we have rapidly constructed 60 overlapping gene libraries that encode zinc finger proteins, randomized variously at the three principal DNA-contacting residues. Expression and screening of the libraries against five possible target DNA sequences generated data points covering a potential 40,000 individual interactions. Comparative analysis of the resulting data enabled direct identification of active proteins. Accuracy of this library analysis methodology was confirmed by both in vitro and in vivo analyses of identified proteins to yield novel zinc finger proteins that bind to their target sequences with high affinity, as indicated by low nanomolar apparent dissociation constants.

Codon-precise, synthetic, antibody fragment libraries built using automated hexamer codon additions and validated through next generation sequencing

We have previously described ProxiMAX, a technology that enables the fabrication of precise, combinatorial gene libraries via codon-by-codon saturation mutagenesis. ProxiMAX was originally performed using manual, enzymatic transfer of codons via blunt-end ligation. Here we present Colibra™: an automated, proprietary version of ProxiMAX used specifically for antibody library generation, in which double-codon hexamers are transferred during the saturation cycling process. The reduction in process complexity, resulting library quality and an unprecedented saturation of up to 24 contiguous codons are described. Utility of the method is demonstrated via fabrication of complementarity determining regions (CDR) in antibody fragment libraries and next generation sequencing (NGS) analysis of their quality and diversity.

Operation sequencing optimization for five-axis prismatic parts using a particle swarm optimization approach

Operation sequencing is one of the crucial tasks in process planning. However, it is an intractable process to identify an optimized operation sequence with minimal machining cost in a vast search space constrained by manufacturing conditions. Also, the information represented by current process plan models for three-axis machining is not sufficient for five-axis machining owing to the two extra degrees of freedom and the difficulty of set-up planning. In this paper, a representation of process plans for five-axis machining is proposed, and the complicated operation sequencing process is modelled as a combinatorial optimization problem. A modern evolutionary algorithm, i.e. the particle swarm optimization (PSO) algorithm, has been employed and modified to solve it effectively. Initial process plan solutions are formed and encoded into particles of the PSO algorithm. The particles 'fly' intelligently in the search space to achieve the best sequence according to the optimization strategies of the PSO algorithm. Meanwhile, to explore the search space comprehensively and to avoid being trapped into local optima, several new operators have been developed to improve the particle movements to form a modified PSO algorithm. A case study used to verify the performance of the modified PSO algorithm shows that the developed PSO can generate satisfactory results in optimizing the process planning problem. © IMechE 2009.

Selection, staging and sequencing in the recent Chinese privatization

Selection in privatization is a decision-making process of choosing state-owned enterprises (SOEs), prioritizing and sequencing privatizing events, and determining the extent of private ownership in partial privatization. We investigate this process in an important but rarely studied case of China. Based on the SOE population over 1998-2008, we track 49,456 wholly SOEs and identify 9,359 privatization cases over time. Our econometric analysis concludes: (i) The privatization selection is a complex decision-making process in which local governments balance between various economic, financial and political objectives. (ii) In the recent Chinese privatization, firm performance relates to the selection, staging and sequencing in privatization in an inverted-U fashion. The worse and the best performing SOEs are more likely to remain state-owned, maintain higher state holding when privatized, and are less likely to be privatized later in time. These patterns suggest the privatization reform slowdown and the underlying changes in the privatization policy.