Using Economic Theory to Guide Numerical Analysis: Solving for Equilibria in Models of Asymmetric First-Price Auctions

In models of first-price auctions, when bidders are ex ante heterogeneous, deriving explicit equilibrium bid functions is typically impossible, so numerical methods are often employed to find approximate solutions. Recent theoretical research concerning asymmetric auctions has determined some properties these bid functions must satisfy when certain conditions are met. Plotting the relative expected pay-offs of bidders is a quick, informative way to decide whether the approximate solutions are consistent with theory. We approximate the (inverse-)bid functions by polynomials and employ theoretical results in two ways: to help solve for the polynomial coefficients and to evaluate qualitatively the appropriateness of a given approximation. We simulate auctions from the approximated solutions and find that, for the examples considered, low-degree polynomial approximations perform poorly and can lead to incorrect policy recommendations concerning auction design, suggesting researchers need to take care to obtain quality solutions.     

An argumentation-oriented multi-agent system for automating the freight planning process

This paper advocates the use of multi-agent systems in the freight forwarding industry. We propose an intelligent mobile agent system to cope with a dynamic freight forwarding environment where up-to-date information is crucial but time-consuming to obtain. A key component of our system is an agent argumentation mechanism that allows decision support agents to discuss, argue, and come to a compromise in order to derive well-explained freight planning solutions. A number of artificial intelligence mechanisms are implemented, namely: (1) a mobile-agent-based automated information gathering mechanism, where designated mobile agents access various websites automatically to gather information (e.g., weather conditions on a candidate route) critical for cargo consolidation and route planning, (2) a fuzzy logics engine for risk evaluation, and (3) a simulated annealing engine for optimizing cargo consolidation. A system prototype is developed and the feasibility of our approach is demonstrated in a case study. A series of experiments are also conducted to evaluate the system’s performance.     

Adsorption of lutein from soybean oil on silicic acid I. Isotherms

Adsorption of lutein from crude soybean oil miscella on dispersed silicic acid resulted in three different Freundlich type isotherms, depending on the amount of adsorbent used. Normally, changing the amount of adsorbent gives a new point on the same isotherm. Further investigation of the lutein adsorption revealed that addition of 1% isopropanol to the hexane solvent and deactivation of the silica acid with water decreased lutein adsorption. Purification of the lutein resulted in increased adsorption, indicating that triglyceride was competing for adsorption sites. The triglyceride competition was confirmed by calculating an adsorption isotherm for triglyceride from crude soybean oil miscella. Use of silicic acid as a column rather than dispersed yielded multiple isotherms for lutein adsorption based on the amount of adsorbent used. Also, lutein adsorption on columns was concentrated at the entrance to the column. Experiments showed that lutein adsorption was not due to partitioning between bound triglyceride and hexane solvent.     

Definition of a multimaterials design method

Although methods of product design and materials selection have been developed, the recent rise of multimaterials (composites, hybrids, etc.) has shown a lack of tools for engineering in this domain. The present contribution aims at the development of a multimaterials design method based on the adaptation of existing methods and on the conclusions of a case study. In comparison with materials selection, the originality of multimaterials design relates to searching materials coupling mechanisms to satisfy a set of requirements. More, it appears that manufacturing process and validation tests are very important points that must be integrated early in the design process.     

Context effects and decompositional choice modeling

This paper describes the application of the extended or universal logit model to decompositional or "stated" choice modeling in order to increase the scope and validity of such choice models. In this approach, choice experiments are designed that permit the estimation of utility functions that include the effects of context variables like choice set composition and decision background. The approach is illustrated with some simple calculated examples concerning consumer choice of shopping center, housing, and transportation mode.An earlier version of this paper was presented at the 30th European Congress, Istanbul, August 1990.     

Nonsmooth model for dynamic simulation of phase changes

Dynamic modeling of processes involving phase changes can be challenging due to changes in the model equations caused by appearance and disappearance of equilibrium phases. Dynamic simulation of these processes requires the ability to detect the change in the number of phases and adapt the model to the new phase regime on the fly. In this work, an easy‐to‐use nonsmooth model for dynamic simulation of processes with vapor‐liquid equilibrium is presented. The presented model does not introduce any auxiliary variables or equations, nor does it require solution of an optimization problem to determine the new phase regime during the dynamic simulation. It can therefore be used for comprehensive simulation of, e.g., distillation columns, where the number of phases present can change during startup and shutdown. The nonsmooth model is illustrated through examples of an evaporator and a distillation column. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3334–3351, 2016     

Particle Swarm Optimisation for Protein Motif Discovery

In this paper, a modified particle swarm optimisation algorithm is proposed for protein sequence motif discovery. Protein sequences are represented as a chain of symbols and a protein sequence motif is a short sequence that exists in most of the protein sequence families. Protein sequence symbols are converted into numbers using a one to one amino acid translation table. The simulation uses EGF protein and C2H2 Zinc Finger protein families obtained from the PROSITE database. Simulation results show that the modified particle swarm optimisation algorithm is effective in obtaining global optimum sequence patterns, achieving 96.9 and 99.5 classification accuracy respectively in EGF and C2H2 Zinc Finger protein families. A better true positive hit result is achieved when compared to the motifs published in PROSITE database.