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Agent-based heuristics for large, multiple-mode, resource-constrained project scheduling problems
No full textIn this dissertation we address large, multiple-mode, resource-constrained project scheduling problems with the objective of minimizing makespan. After noting that projects often fail and new research is needed, we provide the formal definition of the resource-constrained project scheduling problem and review the existing literature. We then introduce a new model based on digital electronics. We conceptualize our model using agent technology and discuss it as extension of existing models with more representational power. We also describe how our model supports distributed planning. After implementing our model, we conduct two computational studies. In the first, we develop two agent types: basic and enhanced where the enhanced agent is more sophisticated in selecting an activity execution mode. We apply these agents to the scheduling of 500 instances of a small project originally published by Maroto and Tormos (1994). We evaluate the performance of the agents in conjunction with their use of eight heuristic prioritization rules: shortest and longest processing time, fewest and most immediate successors, smallest and greatest resource demand, earliest start time, and earliest due date. Our results show that enhanced agents consistently outperform basic agents while the results regarding priority rules were mixed. In the second computational study, we further develop our enhanced agents by providing still more sophisticated mode selection. We also evaluate static versus dynamic prioritization and two more priority rules: shortest and longest duration critical path. For this study we generated 2500, 5000, 7500, and 10000 activity projects. For each of these, we generated networks with complexities of 1.5, 1.8, and 2.1. For these twelve networks, we generated 20 problem instances for every possible combination of resource factor = 0.25, 0.50, 0.75, 1.0 and resource strength = 0.2, 0.5, 0.8. We graphically evaluated scheduling performance, computation times, and failure rates and conducted an extensive statistical analysis. We found that enhanced agents using shortest processing time priority consistently produced the shortest schedules. However, these agents fail more often than basic agents. We found that dynamic prioritization requires more computation time, but provides little improvement in scheduling performance. We conclude this work with suggestions for future research.This item was digitized from a paper original and/or a microfilm copy. If you need higher-resolution images for any content in this item, please contact us at [email protected] file replaced with corrected file September 2023
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Domain-independent semantic concept extraction using corpus linguistics, statistics and artificial intelligence techniques
No full textFor this dissertation two software applications were developed and three experiments were conducted to evaluate the viability of a unique approach to medical information extraction. The first system, the AZ Noun Phraser, was designed as a concept extraction tool. The second application, ANNEE, is a neural net-based entity extraction (EE) system. These two systems were combined to perform concept extraction and semantic classification specifically for use in medical document retrieval systems. The goal of this research was to create a system that automatically (without human interaction) enabled semantic type assignment, such as gene name and disease, to concepts extracted from unstructured medical text documents. Improving conceptual analysis of search phrases has been shown to improve the precision of information retrieval systems. Enabling this capability in the field of medicine can aid medical researchers, doctors and librarians in locating information, potentially improving healthcare decision-making. Due to the flexibility and non-domain specificity of the implementation, these applications have also been successfully deployed in other text retrieval experimentation for law enforcement (Atabakhsh et al., 2001; Hauck, Atabakhsh, Ongvasith, Gupta, & Chen, 2002), medicine (Tolle & Chen, 2000), query expansion (Leroy, Tolle, & Chen, 2000), web document categorization (Chen, Fan, Chau, & Zeng, 2001), Internet spiders (Chau, Zeng, & Chen, 2001), collaborative agents (Chau, Zeng, Chen, Huang, & Hendriawan, 2002), competitive intelligence (Chen, Chau, & Zeng, 2002), and Internet chat-room data visualization (Zhu & Chen, 2001)
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Capacitated rural postman problem with time windows and split delivery
No full textThe importance of effective and efficient distribution is evident from its associated costs. Transportation and shipping alone comprise roughly 15 percent of a product's sales in the U.S. Physical distribution is very energy and labor intensive, which have both become relatively more expensive in the last 10-15 years. Not surprisingly, there is a growing demand for automated planning systems that produce economical routes. Other than the cost savings, introduction of these systems enables companies to maintain a higher level of service for their customers, it makes them less dependent on human planners, it supplies better management information facilities and it makes distribution planning work faster and simpler.This item was digitized from a paper original and/or a microfilm copy. If you need higher-resolution images for any content in this item, please contact us at [email protected] file replaced with corrected file October 2023
The power of foregone payoffs: a mousetracking study
No full textBehavior in two-player laboratory games has been observed to depend upon choices that the other player "could have made," in violation of the principle of subgame perfection. Models of other-regarding preferences that only transform payoffs at end-nodes (e.g. inequality aversion) cannot explain this behavior, and various explanations (e.g. models of intention-based reciprocity) have been proposed. We explore the mechanisms by which foregone payoffs influence decision-making in a variety of two-player, two-stage games using mousetracking, a technology that allows us to observe which payoffs subjects attend to, and for how long, when making strategic decisions
Aggregate Matchings
Get PDFThis paper characterizes the testable implications of stability for aggregate matchings. We consider data on matchings where individuals are aggregated, based on their observable characteristics, into types, and we know how many agents of each type match. We derive stability conditions for an aggregate matching, and, based on these, provide a simple necessary and sufficient condition for an observed aggregate matching to be rationalizable (i.e. such that preferences can be found so that the observed aggregate matching is stable). Subsequently, we derive moment inequalities based on the stability conditions, and provide an empirical illustration using the cross-sectional marriage distributions across the US states
A field study on matching with network externalities
No full textWe study the effects of network externalities on a unique matching protocol for faculty in a large U.S. professional school to offices in a new building. We collected institutional, web, and survey data on faculty's attributes and choices. We first identify the different layers of the social network: institutional affiliation, coauthorships, and friendships. We demonstrate and quantify the effects of network externalities on choices and outcomes. Furthermore, we disentangle the different layers of the social network and quantify their relative impact. Finally, we assess the matching protocol from a welfare perspective. Our study suggests the importance and feasibility of accounting for network externalities in general assignment problems and evaluates a set of techniques that can be employed to this end
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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