Javier Pajares

Simulating the dynamic scheduling of project portfolios

Abstract A main challenge in project management is to provide methodologies that facilitate coordination among the projects in a portfolio or in a firm. Each incoming project in an existing portfolio affects its schedule, the resources availability and the planned performance. There are no analytical solutions for the problem of dynamic scheduling of resources for multiple projects in real time. Mathematical approaches, like integer programming or network based techniques, cannot describe the complexity of real problems (multi-projects environments have many interrelated elements), and have difficulties to adapt the analysis to dynamic changes. We propose a multi-agent system, where projects negotiate the procurement of resources through an auction mechanism all over the portfolio life. Both, projects and resources are modelled as agents. Projects demand resources for fulfilling their scheduled planned work, whereas resources offer their capabilities and workforce. This framework allows project portfolio management and the assessment in the decision of acceptance/rejection new projects.

Explaining the Statistical Features of the Spanish Stock Market from the Bottom-Up

In this paper, we use an agent based artificial stock market to explore the relations between the heterogeneity of investors behaviour and the aggregated behaviour of financial markets. In particular, we want to recover the main statistical features of the Spanish Stock Market, as the high levels of kurtosis, excess volatility, non normality of prices and returns, unit roots and volatility clustering.

The Application of the Viable System Model to Enhance Organizational Resilience

The interest in how to build resilient organizations is increasing in the last two decades. However , there is no formal and accepted framework yet. In this paper, we argue that the application of the principles of the Viable System Model (VSM) improves organizational resilience. We also argue that the VSM constitutes a valid framework to design resilient organizations.

New Insights on the Emergence of Classes Model

We show the results of a detailed replication of the Emergence of Classes Model Axtell et al. (2004). We study the effect of possible biases on the original proposal and we find additional results and conclusions. We also explore the effects of minor changes on the decision rules that agents play.

Impact of Tag Recognition in Economic Decisions

In this paper we replicate the model by Axtell et al. (2000), a game where two agents ask for proportions of the same pie. After simulating the same scenarios, we get the same results, both in the cases of one-agent and two-agent types (tag model). Once we know the model has been properly replicated, we go one step further, by analyzing the influence in the observed behavior of the ‘rational’ decision rule and of the matrix payoff. First, we change the agent’s decision rule, so that agents could decide playing a heuristic which is not so ‘rational’ as the original rule. We also evaluate the dependence of the results on the selected payoff matrix. We conclude that both the decisions rules and the payoff matrix could affect how and when the equilibrium and the segregation emerge in the system. This is particularly interesting for the tag model, as it is related to the role of group recognition in economic decisions.

Selection Processes in a Monopolistic Competition Market

In this paper, we extend the traditional evolutionary model of homogeneous product market by incorporating a particular abstraction of imperfect monopolistic competition borrowed from Dixit and Stiglitz. Specifically, we analyze a formal model of an industry in which a set of heterogeneous firms produce differentiated products; consumers have a preference for variety, and therefore firms enjoy an imperfect monopolistic position in the market. We explore the system dynamics, focusing on how selection processes operate depending on the monopolistic intensity of the market and the heterogeneity of firms.

Innovation and Knowledge Spillovers in a Networked Industry

Knowledge and proximity are key concepts in the Geography of Innovation literature (Boschma, 2005). Innovating processes are uncertain because they often take place under unsure conditions and fierce business competitiveness. Geographical proximity can reduce this uncertainty since it potentially facilitates labor movement and knowledge interchange through personal contacts. Supporting this hypothesis, some scholars have highlighted the greater agglomeration of RD activities in technological industries where knowledge plays a significant economic role (Audretsch and Feldman, 1996a).

Agent Based Modelling and Simulation of an Auction Market for Airport Slots Allocation.

Airport slot allocation is a combinatorial allocation problem involving different complex and autonomous systems. Nowadays, airport slots are allocated in a two-stage process: primary allocation is performed according to a set of administrative rules and for each airport independently, while secondary allocation is based on trading mechanisms. Several studies have raised inefficiencies in these processes. To enhance the airport slot allocation process we use an auction-based market. More specifically, we present an airport slot allocation mechanism based on a price-setting auction that has been implemented and evaluated by means of Agent-Based Modelling (ABM) and simulation techniques. The solutions obtained using our approach are compared and assessed with the ones obtained using linear programing, showing that market mechanisms can be an efficient alternative to the current administrative procedure.

Project Management Methodologies in the Fourth Technological Revolution

We are at the beginning of a new technological revolution, propelled by the development of cyber-physical systems and technologies like Internet of Things, Bid Data, Cloud Computing, 3D Printing, etc. Therefore, we will see an avalanche of projects to implement new business models, products, services and companies. In this paper, we analyse the main characteristics of these projects and we wonder about the appropriate methodologies and managerial styles to lead them. We argue that these projects are complex in nature, according to the current literature on project complexity and thus, classical project management approaches might be unsuitable for managing them. We suggest some clues to seek for new managerial styles, mainly in the literature concerning innovation and new product development and within the “Agile” approach.

A Project Monitoring and Control System Using EVM and Monte Carlo Simulation

Earned Value Management (EVM) tells the project manager whether the project has overruns (costs, delays) or it is running better than planned. But taking into account uncertainty, the methodology does not specify whether the deviation from planned values is within the possible deviations derived from the expected variability of the project. In this paper, a different approach is proposed for monitoring and control projects under uncertainty. The Monte Carlo simulation is used to obtain the “universe” of possible project runs and new and innovative graphs are defined. When the project is running, its current situation can be represented with these graphs, so that it can be established whether the cost or duration of a project is under control at a given time for a given level of confidence.