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In the context of optimization, visualization techniques can be useful for understanding the behaviour of optimization algorithms and can even provide a means to facilitate human interaction with an optimizer. Towards this goal, an image-based visualization framework, without dimension reduction, that visualizes the solutions to large-scale global optimization problems as images is proposed. In the proposed framework, the pixels visualize decision variables while the entire image represents the overall solution quality. This framework affords a number of benefits over existing visualization techniques including enhanced scalability (in terms of the number of decision variables), facilitation of standard image processing techniques, providing nearly infinite benchmark cases, and explicit alignment with human perception. To the best of the authors’ knowledge, this is the first realization of a dimension-preserving, scalable visualization framework that embeds the inherent relationship between decision space and objective space. The proposed framework is utilized with different mapping schemes on an image-reconstruction problem that encompass continuous, discrete, constrained, dynamic, and multi-objective optimization. The proposed framework is then demonstrated on arbitrary benchmark problems with known optima. Experimental results elucidate the flexibility and demonstrate how valuable information about the search process can be gathered via the proposed visualization framework. Results of a user survey strongly support that users perceive a correlation between objective fitness values and the quality of the corresponding images generated by the proposed framework.

Particle swarm optimization (PSO) is a population-based, stochastic search algorithm inspired by the flocking behaviour of birds. The PSO algorithm has been shown to be rather sensitive to its control parameters, and thus, performance may be greatly improved by employing appropriately tuned parameters. However, parameter tuning is typically a time-intensive empirical process. Furthermore, a priori parameter tuning makes the implicit assumption that the optimal parameters of the PSO algorithm are not time-dependent. To address these issues, self-adaptive particle swarm optimization (SAPSO) algorithms adapt their control parameters throughout execution. While there is a wide variety of such SAPSO algorithms in the literature, their behaviours are not well understood. Specifically, it is unknown whether these SAPSO algorithms will even exhibit convergent behaviour. This paper addresses this lack of understanding by investigating the convergence behaviours of 18 SAPSO algorithms both analytically and empirically. This paper also empirically examines whether the adapted parameters reach a stable point and whether the final parameter values adhere to a well-known convergence criterion. The results depict a grim state for SAPSO algorithms; over half of the SAPSO algorithms exhibit divergent behaviour while many others prematurely converge.

Particle swarm optimization (PSO) is a population-based, stochastic optimization technique inspired by the social dynamics of birds. The PSO algorithm is rather sensitive to the control parameters, and thus, there has been a significant amount of research effort devoted to the dynamic adaptation of these parameters. The focus of the adaptive approaches has largely revolved around adapting the inertia weight as it exhibits the clearest relationship with the exploration/exploitation balance of the PSO algorithm. However, despite the significant amount of research efforts, many inertia weight control strategies have not been thoroughly examined analytically nor empirically. Thus, there are a plethora of choices when selecting an inertia weight control strategy, but no study has been comprehensive enough to definitively guide the selection. This paper addresses these issues by first providing an overview of 18 inertia weight control strategies. Secondly, conditions required for the strategies to exhibit convergent behaviour are derived. Finally, the inertia weight control strategies are empirically examined on a suite of 60 benchmark problems. Results of the empirical investigation show that none of the examined strategies, with the exception of a randomly selected inertia weight, even perform on par with a constant inertia weight.

This research identified and analysed a number of inland port sites in the five counties surrounding Los Angeles, using a location-allocation methodology. It also considered the inland ports' potential for integration into a more efficient regional intermodal goods movement system served by the southern California ports of Los Angeles and Long Beach. GIS was used to map the sites where international cargo is processed in the five counties of Los Angeles, Orange, Riverside, San Bernardino, and Ventura. One hundred transportation zones were determined from a truck travel survey conducted by the ports. These zones represent density points for distribution/processing centres. First, a single facility location model was used to define the proximal location of an inland port that minimises the total truck-miles travelled. Then, we extended this model to a series of location-allocation models with up to six inland port locations included. With no inland port (current system), the total daily vehicle-miles travelled (VMT) is 220,100 miles, and the average trip length is 11.6 miles. As more inland ports are added to the location-allocation model, the total truck-miles travelled is reduced significantly. The new system follows the concept of a ‘satellite inland port’, which is based on a hub-and-spoke configuration. Also, with significant reductions in VMT, a proportional amount of congestion relief and air pollution reduction is expected from this new goods movement framework. The results show that the mathematical approach is a useful platform for initial investigations into inland port site selection. Maritime Economics & Logistics (2008) 10, 362–379. doi:10.1057/mel.2008.17

This paper describes research towards the realization of reconfigurable modular automated machines and the associated engineering methods and tools necessary to support their lifecycle needs. UK-based research, in collaboration with the Ford Motor Company and several machine builders, has resulted in the development of full-scale prototype reconfigurable modular automation systems for both engine assembly and machining applications. The implementation of an assembly system is featured in this paper. An engineering environment and associated reconfigurable component-based control system architecture have been created aimed at supporting the lifecycle needs of a new generation of agile automated systems, i.e., providing reconfigurable, easily scalable automated machinery. This approach has the potential to fit within a wider collaborative automation strategy where manufacturing systems are implemented as a conglomerate of distributed, autonomous, and reusable units.

Adsorption of 2-nitrophenol and 4-nitrophenol by titanium dioxide was measured and their photocatalytic oxidation was followed by both HPLC analysis and measurement of the total organic carbon content of the solution. The oxidation follows pseudo-first order kinetics with rate constants that decrease as the nitrophenol concentration increases. However the adsorption constants inferred from the reaction kinetics are inconsistent with those measured in the adsorption experiments, even though the relative amounts of reaction intermediates remain low. We conclude that the decrease in rate constant cannot be explained by a Langmuir–Hinshelwood model. Instead we suggest that the strong, but differing, UV absorption by nitrophenols lowers the effective UV flux at the catalyst surface and that the greater absorption of more concentrated solutions is primarily responsible for the apparent decrease in rate constant. A simple treatment of this absorption adequately describes the observed changes in rate. The quantitative effect of UV absorption depends on the lamp and on the reactor optics. It his suggested that variations are responsible both for differences in the reported relative oxidation rates of the two isomers, and for the different conclusions reported with respect to the effect of pH on oxidation rate.

The Community Rainforest Reforestation Program (CRRP) in north Queensland, Australia, was a multi-faceted experiment in facilitating farm forestry. It was motivated in part by the World Heritage listing of the Wet Tropics of Queensland rainforests, which removed a large resource from the timber industry. Survey results indicate that some landholders have applied high-quality silvicultural management to their stands with a view to timber production, while others have been more interested in wildlife habitat and other non-wood benefits. Although not necessarily a success in terms of its stated goals, the program can be credited with a number of achievements. It yielded valuable experience in growing native tree species, job training for young unemployed people, and collaboration between Federal, State and local government in forest industry development. The program generated positive environmental outcomes and lessons for future timber and environmental planting programs on private lands. While the area planted and quantity of timber produced will fall far short of initial expectations, and some limitations arose with the job training activities, it nevertheless appears to have been a worthwhile project.

Although commercial health insurance records are a potentially valuable source of data for cancer outcomes studies, the accuracy of administrative codes for identifying persons with cancer is unknown. The objective of this study was to determine the accuracy of administrative codes for identifying persons with newly diagnosed colorectal cancer. The Washington state SEER cancer registry was linked with enrollment files from two large commercial health plans: a fee-for-service plan and a staff-model HMO with combined enrollment of more than 1.7 million. The accuracy of ICD-9 codes for colorectal cancer for enrollees diagnosed between January 1, 1996 and December 31, 1999 was compared for each plan, using SEER records as the “gold standard.”

The rates of carburization by mixtures of CO, CO2, H2 and H2O in N2 have been measured gravimetrically at 925 °. The rate equation which best describes the experimental data is based on a mechanism which involves a rapid surface dissociation of CO into carbon and oxygen atoms, and a subsequent rate determining step between this atomic oxygen and either CO or H2. The CO-H2 system carburizes much faster than CO alone, because H2 combines faster with atomic oxygen than does CO. The carburizing rate constant for CO-H2 is 44 times that for CO alone. The mechanism is confirmed by the additivity of the separate rates for the CO-H2 mixtures and for CO alone.

Studies using 1010 steel shimstock in a controlled atmosphere tubular furnace have allowed rate constants to be determined for a number of important carburizing and decarburizing reactions. Carburizing data obtained in a small commercial furnace confirm that the combination of CO and H2 to form C and H2O is the major carbon transfer reaction to the parts in a typical furnace system. The hydrocarbon injected in the furnace for enrichment deposits carbon on the heating surfaces initially as a result of catalytic cracking reactions. Due to the temperature differential between heating surfaces and parts, the CO-H2 reaction acts as a “carbon pump” in transferring this carbon to the reactive surface of the parts to be carburized. Carbon control by monitoring the concentration of CO and CO2 or CO, H2, and H2O is most efficient in the later stages of a typical furnace cycle as the carbon concentration at the surface of the parts approaches the carbon potential in the gas phase.

Rates of carburization of low-carbon steel by CH4, C2H2, C2H4, C2H6, and C3H8 in N2 have been measured gravimetrically at 850 °C and 925 °C. Methane appears to be the slowest and acetylene the fastest carburizing agent among the hydrocarbons tested. Hydrogen enhances the rates of carburizing of all hydrocarbons, probably by removing adsorbed oxygen from the steel surface. At high H2/CH4 ratios, H2 will decarburize steel at 925 °C. All hydrocarbons, including CH2, are also involved in gas phase reactions. These reactions may lead to the formation of soot at carburizing temperatures. Sooting is inhibited by the addition of H2 to hydrocarbon-nitrogen gas mixtures. Acetylene appears to be a key intermediate for the formation of soot as the final product of hydrocarbon reactions in the gas phase.

Summary: Recently a soybean oil emulsion (Intralipid) (IL) has been released in the United States for use as a parenteral nutrient. The study reported here was undertaken to determine the effect of ingestion of IL on the synthesis and secretion of the second (C2) and fourth (C4) components of complement by guinea pig peritoneal macrophages in vitro. Cells exposed to IL had extensive Oil Red 0-positive granular-appearing accumulations of neutral lipid within the cytoplasm. Control cells did not stain with Oil Red 0. Incubation of the cells with concentrations of IL from 2.3-37.5 mg/100 ml resulted in a significant decrease in the production of both C2 and C4, which could not be explained by variability between plates. The decrease in total C2 or C4 production by cells incubated with IL for 4 hr was similar to the decrease in production by cells incubated with IL for 48 hr. Several lines of evidence indicated that the decrease of C2 or C4 was the result of decreased synthesis of these proteins and not interference of IL with the detection of the proteins or their secretion from the cells. Exposure of the cells to IL at all concentrations caused reduction of the number of cells having pseudopodia and a rounding-up of the cells. IL did not affect the rate of detachment of the cells from the plates through the 48-hr incubation period or the ability of the cells to exclude trypan blue. Total protein synthesis and total lysozyme production by control and IL-treated cells was similar.

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