Methods of improving scalability in online auctions include limiting the number of bidding opportunities, providing price information to users, and recommending auctions that may be of interest to the users. We constructed an experimental prototype auction system in the context of reverse logistics for electronics products. Experiments were designed to test the effects of the number of trading opportunities and the amount of previous price and bid information presented to users. The participants' profits improved with the number of trading opportunities but showed mixed effects for increasing price and bid information. Some measures of market robustness and bid/price dynamics were affected by the information in unexpected ways. The induction of decision trees for an auction recommender is discussed along with the use of attribute selection to reduce the size of the tree.
We propose a new randomized method for solving global optimization problems. This method, the Nested Partitions (NP) method, systematically partitions the feasible region and concentrates the search in regions that are the most promising. The most promising region is selected in each iteration based on information obtained from random sampling of the entire feasible region and local search. The method hence combines global and local search. We first develop the method for discrete problems and then show that the method can be extended to continuous global optimization. The method is shown to converge with probability one to a global optimum in finite time. In addition, we provide bounds on the expected number of iterations required for convergence, and we suggest two stopping criteria. Numerical examples are also presented to demonstrate the effectiveness of the method.
Objective: To assess the proportion of PBC patients with a biochemical response to ursodeoxycholic acid (UDCA) in a population-based cohort and the association of biochemical response with outcomes. Methods: All patients diagnosed with PBC in Iceland from 1991-2015 were identified. Patients taking UDCA for an adequate period of time were analyzed for treatment response according to the Barcelona, Paris I, Paris II and Toronto criteria and outcomes. Results: Overall 182 females and 40 males were diagnosed with PBC and 135 patients were treated with UDCA. Overall 99 (73%) patients had adequate data on UDCA treatment and results of liver tests to assess biochemical response according to the Barcelona criteria, 95 (70%) according to the Toronto criterion and 85 (63%) according to the Paris I and II criteria. In all 74% (n = 63), 67% (n = 64), 54% (n = 53) and 46% (n = 39) responded to treatment according to the Paris I, Toronto, Barcelona and Paris II criteria. Among nonresponders according to the Paris I, Toronto, Paris II and Barcelona criteria, 50%, 39%, 33% and 30% developed cirrhosis versus 10%, 6%, 5% and 11% of responders, HR 5.36 (p = .002), 6.61 (p = .002), 10.94 (p = .003) and 2.21(p = .11), respectively. Age-adjusted mortality was significantly lower among responders according to the Paris I and Paris II criteria, HR 0.33 (p = .02) and 0.31 (p = .02), respectively. Conclusion: Development of cirrhosis and higher mortality was significantly associated with a lack of biochemical response to UDCA. Frequent development of cirrhosis and increased mortality in nonresponders underlines the need for a more effective therapy than UDCA for this sizeable subgroup of patients.
Simulation optimization has received considerable attention from both simulation researchers and practitioners. In this tutorial we present a broad introduction to simulation optimization and the many techniques that have been suggested to solve simulation optimization problems. Both continuous and discrete problems are discussed, but an emphasis is placed on discrete problems and practical methods for addressing such problems.
The nested partitions method is a flexible and effective framework of optimizing large-scale problems with combinatorial structure. In this paper we consider the nested partitions method for simulation optimization and propose a new variant that uses inheritance to speed convergence. The new nested partitions method with inheritance algorithm performs well for when applied to test problems but it also calls for new analysis of convergence.
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