A multi-agent system using iterative bidding mechanism to enhance manufacturing agility

The global market has become increasingly dynamic, unpredictable and customer-driven. This has led to rising rates of new product introduction and turbulent demand patterns across product mixes. As a result, manufacturing enterprises were facing mounting challenges to be agile and responsive to cope with market changes, so as to achieve the competitiveness of producing and delivering products to the market timely and cost-effectively. This paper introduces a currency-based iterative agent bidding mechanism to effectively and cost-efficiently integrate the activities associated with production planning and control, so as to achieve an optimised process plan and schedule. The aim is to enhance the agility of manufacturing systems to accommodate dynamic changes in the market and production. The iterative bidding mechanism is executed based on currency-like metrics; each operation to be performed is assigned with a virtual currency value and agents bid for the operation if they make a virtual profit based on this value. These currency values are optimised iteratively and so does the bidding process based on new sets of values. This is aimed at obtaining better and better production plans, leading to near-optimality. A genetic algorithm is proposed to optimise the currency values at each iteration. In this paper, the implementation of the mechanism and the test case simulation results are also discussed. © 2012 Elsevier Ltd. All rights reserved.

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.

Decision support system for vendor managed inventory supply chain:a case study

Vendor-managed inventory (VMI) is a widely used collaborative inventory management policy in which manufacturers manages the inventory of retailers and takes responsibility for making decisions related to the timing and extent of inventory replenishment. VMI partnerships help organisations to reduce demand variability, inventory holding and distribution costs. This study provides empirical evidence that significant economic benefits can be achieved with the use of a genetic algorithm (GA)-based decision support system (DSS) in a VMI supply chain. A two-stage serial supply chain in which retailers and their supplier are operating VMI in an uncertain demand environment is studied. Performance was measured in terms of cost, profit, stockouts and service levels. The results generated from GA-based model were compared to traditional alternatives. The study found that the GA-based approach outperformed traditional methods and its use can be economically justified in small- and medium-sized enterprises (SMEs).