An Evolutionary Approach to Active Robust Multiobjective Optimisation

An Active Robust Optimisation Problem (AROP) aims at finding robust adaptable solutions, i.e. solutions that actively gain robustness to environmental changes through adaptation. Existing AROP studies have considered only a single performance objective. This study extends the Active Robust Optimisation methodology to deal with problems with more than one objective. Once multiple objectives are considered, the optimal performance for every uncertain parameter setting is a set of configurations, offering different trade-offs between the objectives. To evaluate and compare solutions to this type of problems, we suggest a robustness indicator that uses a scalarising function combining the main aims of multi-objective optimisation: proximity, diversity and pertinence. The Active Robust Multi-objective Optimisation Problem is formulated in this study, and an evolutionary algorithm that uses the hypervolume measure as a scalarasing function is suggested in order to solve it. Proof-of-concept results are demonstrated using a simplified gearbox optimisation problem for an uncertain load demand

A novel mutation of the calcium sensing receptor gene is associated with chronic pancreatitis in a family with heterozygous SPINK1 mutations

BACKGROUND: The role of mutations in the serine protease inhibitor Kazal type 1 (SPINK1) gene in chronic pancreatitis is still a matter of debate. Active SPINK1 is thought to antagonize activated trypsin. Cases of SPINK1 mutations, especially N34S, have been reported in a subset of patients with idiopathic chronic pancreatitis. However, the inheritance pattern is still unknown. Some cases with N34S heterozygosity have been reported with and without evidence for CP indicating neither an autosomal recessive nor dominant trait. Therefore SPINK1 mutations have been postulated to act as a disease modifier requiring additional mutations in a more complex genetic model. Familial hypocalciuric hypercalcemia (FHH) caused by heterozygous inactivating mutations in the calcium sensing receptor (CASR) gene is considered a benign disorder with elevated plasma calcium levels. Although hypercalcemia represents a risk factor for pancreatitis, increased rates of pancreatitis in patients with FHH have not been reported thus far. METHODS: We studied a family with a FHH-related hypercalcemia and chronic pancreatitis. DNA samples were analysed for mutations within the cationic trypsinogen (N29I, R122H) and SPINK1 (N34S) gene using melting curve analysis. Mutations within CASR gene were identified by DNA sequencing. RESULTS: A N34S SPINK1 mutation was found in all screened family members. However, only two family members developed chronic pancreatitis. These patients also had FHH caused by a novel, sporadic mutation in the CASR gene (518T>C) leading to an amino acid exchange (leucine->proline) in the extracellular domain of the CASR protein. CONCLUSION: Mutations in the calcium sensing receptor gene might represent a novel as yet unidentified predisposing factor which may lead to an increased susceptibility for chronic pancreatitis. Moreover, this family analysis supports the hypothesis that SPINK1 mutations act as disease modifier and suggests an even more complex genetic model in SPINK1 related chronic pancreatitis

Emerging Multiple-Issue E-Auctions

We review the emerging field of multiple issue e-auctions and discuss their design features and performance criteria. We primarily consider B2B transactions in a reverse auction, that is, a procurement setting. In traditional auctions, the matching of buyers and sellers is typically based just on price. However, when there are quality and other differences in the merchandise and differences in the terms of the transaction, which are common in Request for Quotes, additional issues besides price should be considered. Such multiple issue, multiple unit e-auctions/negotiations, and their characteristics are the focus of our paper. We also discuss the role that OR has played and undoubtedly will play in the design and implementation of such e-auctions

Qualitative One-to-Many Multi-Issue Negotiation: Approximating the QVA

When there is one buyer interested in obtaining a service from one of a set of sellers, multi-attribute or multi-issue auctions can ensure an allocation that is efficient. Even when there is no transferable utility (e.g., money), a recent qualitative version of the Vickrey auction may be used, the QVA, to obtain a Pareto-efficient outcome where the best seller wins. However, auctions generally require that the preferences of at least one party participating in the auction are publicly known, while often making this information public is costly, undesirable, or even impossible. It would therefore be useful to have a method that does not impose such a requirement, but is still able to approximate the outcome of such an auction. The main question addressed here is whether the Pareto-efficient best-seller outcome in multi-issue settings without transferable utility (such as determined by the QVA) can be reasonably approximated by multi-bilateral closed negotiation between a buyer and multiple sellers. In these closed negotiations parties do not reveal their preferences explicitly, but make alternating offers. The main idea is to have multiple rounds of such negotiations. We study three different variants of such a protocol: one that restricts the set of allowed offers for both the buyer and the seller, one where the winning offer is announced after every round, and one where the sellers are only told whether they have won or not after every round. It is shown experimentally that this protocol enables agents that can learn preferences to obtain agreements that approximate the Pareto-efficient best-seller outcome as defined by the auction mechanism. We also show that the strategy that exploits such a learning capability in negotiation is robust against and dominates a Zero Intelligence strategy. It thus follows that the requirement to publicly announce preferences can be removed when negotiating parties are equipped with the proper learning capabilities and negotiate using the proposed multi-round multi-bilateral negotiation protocol.Intelligent SystemsElectrical Engineering, Mathematics and Computer Scienc