Emergence of population structure in socio-cognitively inspired ant colony optimization

A metaheuristic proposed by us recently, Ant Colony  Optimization (ACO) hybridized with socio-cognitive inspirations, turned out to generate interesting results compared to classic ACO. Even though it does not always find better solutions to the considered problems, it usually finds sub-optimal solutions  usually. Moreover, instead of a trial-and-error approach to configure the parameters of the ant species in the population, in our approach, the actual structure of the population emerges from predefined species-to-species ant migration strategies. Experimental results of our approach are compared against classic ACO and selected socio-cognitive versions of this algorithm

The application of set-based concurrent engineering to enhance the design performance of surface jet pump

Set-Based Concurrent Engineering (SBCE) is an approach that has the capability to improve the efficiencies of the product development process. SBCE provides an environment where design space is explored thoroughly which lead to enhance innovation. This is achieved by considering an alternative set of solutions after gaining the right knowledge to support decision to narrow down the set of solutions until the single optimal design solution is reached. This paper presents a novel application SBCE in order to generate alternative design to enhance the efficiency of the Surface Jet Pump (SJP) in term of its productivity and performance of producing the oil and gas in oil and gas well

Trade-off curves applications to support set-based design of a surface jet pump

Knowledge has become the most important asset of companies, especially in improving their product development processes. The set-based design approach is an efficient way of designing high quality, optimised designs. However, it requires a proven knowledge environment. Trade-off curves (ToCs) have the capability of providing the right knowledge and displaying it in a visual form. Although there are a few applications of ToCs that have recently been published in the literature, none of them demonstrates an integrated implementation of ToCs throughout the SBCE process. This paper presents the integrated use of ToCs, based on both physics-knowledge and proven knowledge, in order to compare and narrow down the design-set and to achieve an optimal design solution. These are key activities of the SBCE process model. Since an accurate, documented and visual knowledge environment is created by the use of ToCs within SBCE, the integrated approach proposed in this paper plays a vital role in eliminating the need for prototyping and testing at the early stages of product development. The integrated approach was implemented in an industrial case study for a surface jet pump. Surface jet pumps are used to increase the production rate of low-pressure oil/gas wells. It has been found that through ToCs, the conflicting relationships between the characteristics of the product can be understood and communicated effectively among the designers. This facilitated the decision-making on an optimal design solution in a remarkably short period of time. Furthermore, the surface jet pump resulting from the case study achieved an increase of the oil/gas production by nearly 60%

Emergence of population structure in socio-cognitively inspired ant colony optimization

A metaheuristic proposed by us recently, Ant Colony  Optimization (ACO) hybridized with socio-cognitive inspirations, turned out to generate interesting results compared to classic ACO. Even though it does not always find better solutions to the considered problems, it usually finds sub-optimal solutions  usually. Moreover, instead of a trial-and-error approach to configure the parameters of the ant species in the population, in our approach, the actual structure of the population emerges from predefined species-to-species ant migration strategies. Experimental results of our approach are compared against classic ACO and selected socio-cognitive versions of this algorithm

The set-based concurrent engineering application: a process of identifying the potential benefits in the surface jet pump case study

The Set-Based Concurrent Engineering (SBCE) is the methodology that can improve the efficiencies and effectiveness of product development. It is found that the SBCE approach provided a suitable knowledge environment to support decision making throughout the development process. This paper presents the potential tangible benefits gained from the application of the SBCE in an industrial case study of a Surface Jet Pump (SJP) that is used to revive the production of oil/gas from the dead wells. The well-structured SBCE process model and the process of identifying the potential benefits proposed in this paper will clarify the gap in the development of the SBCE in the company. The potential tangible benefits are established in a few key areas such as product innovation, product performance, manufacturing cost, and project success rate

Emergence of population structure in socio-cognitively inspired Ant Colony Optimization

A metaheuristic proposed by us recently, Ant Colony Optimization (ACO) hybridized with socio-cognitive inspirations, turned out to generate interesting results compared to classic ACO. Even though it does not always find better solutions to the considered problems, it usually finds sub-optimal solutions usually. Moreover, instead of a trial-and-error approach to configure the parameters of the ant species in the population, in our approach, the actual structure of the population emerges from predefined species-to-species ant migration strategies. Experimental results of our approach are compared against classic ACO and selected socio-cognitive versions of this algorithm