On the suitability of Yule process to stochastically model some properties of object-oriented systems

We present a study of three large object-oriented software systems—VisualWorks Smalltalk, Java JDK and Eclipse—searching for scaling laws in some of their properties. We study four system properties related to code production, namely the inheritance hierarchies, the naming of variables and methods, and the calls to methods. We systematically found power-law distributions in these properties, most of which have never been reported before. We were also able to statistically model the programming activities leading to the studied properties as Yule processes, with very good correspondence between empirical data and the prediction of Yule model. The fact that a design and optimization process like software development can be modeled on the large with the laws of statistical physics poses intriguing issues to software engineers, and could be exploited for finding new metrics and quality measures.     

Design issues for combinatorial auctions

Combinatorial auctions are an important class of market mechanisms in which participants are allowed to bid on bundles of multiple heterogeneous items. In this paper, we discuss several complex issues that are encountered in the design of combinatorial auctions. These issues are related to the formulation of the winner determination problem, the expression of combined bids, the design of progressive combinatorial auctions that require less information revelation, and the need for decision support tools to help participants make profitable bidding decisions. For each issue, we survey the existing literature and propose avenues for further research.Received: April 2003, Revised: July 2003, AMS classification: 91B26, 90BXX, 90C27All correspondence to:Jawad Abrache     

Model management systems: A survey

This paper provides a survey of model management literature within the mathematical modeling domain. The first part of the survey is a review and a summary of the literature. After giving some basic definitions of modeling, modeling life cycle, and model management, two representative algebraic modeling languages followed by three approaches to modeling are introduced. These approaches are database, graph-based, and knowledge-based. The discussion is followed by a review of two specialized model management systems. The second part of the survey is a categorization of various modeling systems based on the modeling functions they provide and some of their features. These functions include life cycle support and model base administration. The degree of model independence provided by model management systems and the implemented environment systems is also summarized. The last part of the paper provides directions for future research.     

Representation of time in mathematical programming modeling languages

Time-staged mathematical programming models have a planning horizon that is divided into a sequence of consecutive time periods. For the modeling of this sequence of time periods the use of calendars is proposed as an additional set concept for mathematical programming modeling languages. The definition of calendars is based on familiar notions such as set, ordering, interval length and functions. A calendar is an interval set and can be used to verify automatically the proper time referencing in stock balances. When a calendar is also a difference set, then backward and forward time referencing can be stated with the explicit use of time units. For models with a rolling horizon, concise and flexible ways to specify the structure of calendars are presented. The aggregation of raw data into model parameter values is supported by linking calendars that represent different time scales. The influence of the proposed calendar concept on the human ability to understand, maintain and verify models is analyzed throughout the paper on the basis of selected examples.     

Bidding in sequential electricity markets: The Nordic case

For electricity market participants trading in sequential markets with differences in price levels and risk exposure, it is relevant to analyze the potential of coordinated bidding. We consider a Nordic power producer who engages in the day-ahead spot market and the hour-ahead balancing market. In both markets, clearing prices and dispatched volumes are unknown at the time of bidding. However, in the balancing market, the market participant faces an additional risk of not being dispatched. Taking into account the sequential clearing of these markets and the gradual realization of market prices, we formulate the bidding problem as a multi-stage stochastic program. We investigate whether higher risk exposure may cause hesitation to bid into the balancing market. Furthermore, we quantify the gain from coordinated bidding, and by deriving bounds on this gain, assess the performance of alternative bidding strategies used in practice.