Jarosław Stańczak

Simulation of an uncertain emission market for greenhouse gases using agent-based methods

The paper presents the problem of a simulation of the greenhouse gases emission permits market where only low accuracy emission amounts are known. An organization of the market with uncertain emissions is proposed and trading rules for individual market participants are discussed. Simulation of the market is based on a multi-agent system. Negotiation of purchase/sale prices between the parties are introduced, where the trading parties adopt one of two options: (i) bilateral negotiations, and (ii) sealed bid reverse auctions. Results of simulation runs show trajectories of transaction prices, as well as probability distributions of learning agents’ bidding prices.

Dynamic Pricing and Balancing Mechanism for a Microgrid Electricity Market

The trading is a well known, easy and efficient method of distributing goods. Energy cannot be stored efficiently, which implies that supply and demand of power has to be balanced at all times; this adds complexity to the trading of electric power. Introduction of microgrids, with internal balancing of power and trading with external power grid, brings many questions about power distribution, sharing of costs and revenues. Using market mechanism for such purpose seems appropriate. In this article we present an example of balancing a microgrid with its own energy production sources and connected to a higher voltage distribution grid, by introduction of the continuous double auction market with agents following the Adaptive-Aggressive Strategy.

Separable Decomposition of Graph Using α-cliques

The article deals with an evolutionary based method to decompose graph into strongly connected structures, we called α-cliques. The α-clique is a generalization of a clique concept with the introduction of parameter α. Using this parameter it is possible to control the degree (or strength) of connections among vertices (nodes) of this sub-graph structure. The evolutionary approach is proposed as a method that enables to find separate α-cliques that cover the set of graph vertices.

Evolutionary Method in Grouping of Units

This paper deals with the clustering problem, where an order of elements plays a pivotal role. This formulation is very usable for wide range of Decision Support System (DSS) applications. The proposed clustering method consists of two stages. The first is a stage of data matrix reorganization, using a specialized evolutionary algorithm. The second stage is a final clustering step and is performed using a simple clustering method.

Multiobjective optimization in the Airport Gate Assignment Problem, exact versus evolutionary multiobjective optimization

In this paper, we approach the Airport Gate Assignment Problem by Multiobjective Optimization as well as Evolutionary Multi-objective Optimization. We solve a bi-criteria formulation of this problem by the commercial mixedinteger programming solver CPLEX and a dedicated Evolutionary Multiobjective Optimization algorithm. To deal with multiple objectives, we apply a methodology that we developed earlier to capture decision-maker preferences in multi-objective environments. We present the results of numerical tests for these two approaches.

Reverse clustering: an outline for a concept and its use

ABSTRACT In this study, a new perspective on the application of the clustering approach is proposed. The perspective aims to identify the values of the parameters of clustering, including the choice of the algorithm itself, which lead to a possibly faithful rendering of a partition of data, which is known a priori. Motivation and possible interpretations are discussed which can be associated with such a reverse identification process. The essential motivation is associated, but not limited, to the primary objective of cluster analysis, i.e. gaining insight into the structure of the given data-set or family of data-sets. We propose to use evolutionary strategies for reverse analysis to be carried out in view of the characteristics of the problem considered. The concept and the feasibility of the proposed computational approach are illustrated by the analysis of an exemplary data-set. The preliminary results obtained are promising in both technical and cognitive terms.

Using a Reverse Engineering Type Paradigm in Clustering. An Evolutionary Programming Based Approach

The aim of this work is to propose a novel view on the well-known clustering approach that is here dealt with from a different perspective. We consider a kind of a reverse engineering related approach, which basically consists in discovering the broadly meant values of the parameters of the clustering algorithm, including the choice of the algorithm itself, or even – more generally – its class, and some other parameters, that have possibly led to a given partition of data, known a priori. We discuss the motivation and possible interpretations related to such a novel reversed process. In fact the main motivation is gaining insight into the structure of the given data set or even a family of data sets. The use of the evolutionary strategies is proposed to computationally implement such a reverse analysis. The idea and feasibility of the proposed computational approach is illustrated on two benchmark type data sets. The preliminary results obtained are promising in terms of a balance between analytic and computational effectiveness and efficiency, quality of results obtained and their comprehensiveness and intuitive appeal, a high application potential, as well as possibilities for further extensions.

The Problem of Distribution of Park-and-Ride Car Parks in Warsaw

The development of cities and agglomerations brings new problems to be solved. One of them is the excessive road traffic and the related air pollution. Heavy traffic causes congestions and thus increases the pollution level, because one of the most significant sources of air pollution are car exhaust gases. It is known that the public transport produces less pollution per one passenger then the private one. On the basis of this fact the idea of the Park-and-Ride (P&R or P+R) was developed, where commuters travel to the borders of the city by their cars and from there they continue their trip by public transportation. In this work, we will concentrate on finding the best localizations for P&R points. Our approach is composed of two steps. In the first step, a number of communication hubs is selected where P&R can be located (feasibility analysis). In the second step a subset of hubs is chosen to actually have P&R points built (commuters convenience analysis). We solve the P&R location problem on the first step using some aspects of the Hub and Spoke method by applying a specialized evolutionary algorithm. As the problem of the second step is rather small, we propose to have it solved by experts.

Graph based approach to the minimum hub problem in transportation network

In this paper we consider a hub location problem in a real multimodal public transportation network. This problem is also known as the park-and-ride problem. Hubs stations are special facilities that serve as switches in such a network. In practice the set of hubs has a strategic importance, because all of the traffic that passes through the network can be controlled by these elements. From the theoretical point of view, the minimal hub problem is NP hard. Two different approaches to this problem are presented. The first group of methods bases on the greedy algorithms. In the second group the evolutionary strategy is used. The computational results for these algorithms proved a significant efficiency, what can be clearly expressed in terms of an input data reduction and also in quality measure values for the obtained solutions of this problem.

The Kernel and Shell Structure as a Tool for Improving the Graph of Transportation Connections

A model of a transportation system is expected to be useful in simulations of a real system to solve given transportation tasks. A connection graph is routinely used to describe a transportation system. Vertices can be train stations, bus stops, airports etc. The edges show direct connections between vertices. A direct approach can be difficult and computational problems can arise in attempts to organize or optimize such a transportation system. Therefore, a method for aggregating such graphs was introduced, using a general kernel and shell structure and its particular instances: i i-clique structured graphs of connections and a hub and spoke transformation of the source graph. These structures enable the concentration and ordering of transport between vertices and reduction of the analyzed graph. To obtain the desired structures, several versions of a specialized evolutionary algorithm were developed and applied.