AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Self-Evaluation Applied Mathematics 2003-2008 University of Twente

This report contains the self-study for the research assessment of the Department of Applied Mathematics (AM) of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente (UT). The report provides the information for the Research Assessment Committee for Applied Mathematics, dealing with mathematical sciences at the three universities of technology in the Netherlands. It describes the state of affairs pertaining to the period 1 January 2003 to 31 December 2008

Environmental analysis for application layer networks

Die zunehmende Vernetzung von Rechnern über das Internet lies die Vision von Application Layer Netzwerken aufkommen. Sie umfassen Overlay Netzwerke wie beispielsweise Peer-to-Peer Netzwerke und Grid Infrastrukturen unter Verwendung des TCP/IP Protokolls. Ihre gemeinsame Eigenschaft ist die redundante, verteilte Bereitstellung und der Zugang zu Daten-, Rechen- und Anwendungsdiensten, während sie die Heterogenität der Infrastruktur vor dem Nutzer verbergen. In dieser Arbeit werden die Anforderungen, die diese Netzwerke an ökonomische Allokationsmechanismen stellen, untersucht. Die Analyse erfolgt anhand eines Marktanalyseprozesses für einen zentralen Auktionsmechanismus und einen katallaktischen Markt. --Grid Computing

Modelling rail track deterioration and maintenance: current practices and future needs

As commercialisation and privatisation of railway systems reach the political agendas in a number of countries, including Australia, the separation of infrastructure from operating business dictates that track costs need to be shared on an equitable basis. There is also a world-wide trend towards increased pressures on rail track infrastructure through increases in axle loads and train speeds. Such productivity and customer service driven pressures inevitably lead to reductions in the life of track components and increases in track maintenance costs. This paper provides a state-of-the-art review of track degradation modeling, as well as an overview of track maintenance decision support systems currently in use in North America and Europe. The essential elements of a maintenance optimisation model currently under development are also highlighted

A multi-agent system with application in project scheduling

The new economic and social dynamics increase project complexity and makes scheduling problems more difficult, therefore scheduling requires more versatile solutions as Multi Agent Systems (MAS). In this paper the authors analyze the implementation of a Multi-Agent System (MAS) considering two scheduling problems: TCPSP (Time-Constrained Project Scheduling), and RCPSP (Resource-Constrained Project Scheduling). The authors propose an improved BDI (Beliefs, Desires, and Intentions) model and present the first the MAS implementation results in JADE platform.multi-agent architecture, scheduling, project management, BDI architecture, JADE.

Understanding construction delay analysis and the role of pre-construction programming

Copyright © 2013, American Society of Civil Engineers. This is the author's accepted manuscript. The final published article is available from the link below.Modern construction projects commonly suffer from delay in their completions. The resolution of time and cost claims consequently flowing from such delays continues to remain a difficult undertaking for all project parties. A common approach often relied on by contractors and their employers (or their representatives) to resolve this matter involves applying various delay analysis techniques, which are all based on construction programs originally developed for managing the project. However, evidence from literature suggests that the reliability of these techniques in ensuring successful claims resolution are often undermined by the nature and quality of the underlying program used. As part of a wider research carried out on delay and disruption analysis in practice, this paper reports on an aspect of the study aimed at exploring preconstruction stage programming issues that affect delay claims resolutions. This aspect is based on an in-depth interview with experienced construction planning engineers in the United Kingdom, conducted after an initial large-scale survey on delay and disruption techniques usage. Summary of key findings and conclusions include: (1) most contractors prefer to use linked bar chart format for their baseline programs over conventional critical path method (CPM) networks; (2) baseline programs are developed using planning software packages. Some of these pose difficulties when employed for most delay analysis techniques, except for simpler ones; (3) manpower loading graphs are not commonly developed as part of the main deliverables during preconstruction stage planning. As a result, most programs are not subjected to resource loading and leveling for them to accurately reflect planned resource usage on site. This practice has detrimental effects on the reliability of baseline programs in their use for resolving delay claims; and (4) baseline program development involves many different experts within construction organizations as expected, but with very little involvement of the employer or its representative. Active client involvement is however quite important as it would facilitate quick program approval/acceptance before construction, a necessary requirement for early delay claims settlement, which otherwise are often left unresolved long after the delaying events with the potential of generating into expensive disputes. The study results provide a better understanding of the key issues that need attention if improvements are to be made in delay claim resolutions. Additional research focusing on the testing of these results using a much larger sample and rigorous statistical analysis for generalization purposes would be helpful in advancing the limited knowledge of this subject matter

Multiobjective strategies for New Product Development in the pharmaceutical industry

New Product Development (NPD) constitutes a challenging problem in the pharmaceutical industry, due to the characteristics of the development pipeline. Formally, the NPD problem can be stated as follows: select a set of R&D projects from a pool of candidate projects in order to satisfy several criteria (economic profitability, time to market) while coping with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to develop once target molecules have been identified, their order and the level of resources to assign. In this context, the proposed approach combines discrete event stochastic simulation (Monte Carlo approach) with multiobjective genetic algorithms (NSGAII type, Non-Sorted Genetic Algorithm II) to optimize the highly combinatorial portfolio management problem. In that context, Genetic Algorithms (GAs) are particularly attractive for treating this kind of problem, due to their ability to directly lead to the so-called Pareto front and to account for the combinatorial aspect. This work is illustrated with a study case involving nine interdependent new product candidates targeting three diseases. An analysis is performed for this test bench on the different pairs of criteria both for the bi- and tricriteria optimization: large portfolios cause resource queues and delays time to launch and are eliminated by the bi- and tricriteria optimization strategy. The optimization strategy is thus interesting to detect the sequence candidates. Time is an important criterion to consider simultaneously with NPV and risk criteria. The order in which drugs are released in the pipeline is of great importance as with scheduling problems