Local Optima Networks, Landscape Autocorrelation and Heuristic Search Performance

Chicano, F., Daolio F., Ochoa G., Vérel S., Tomassini M., & Alba E. (2012). Local Optima Networks, Landscape Autocorrelation and Heuristic Search Performance. (Coello, C. A. Coello, Cutello V., Deb K., Forrest S., Nicosia G., & Pavone M., Ed.).Parallel Problem Solving from Nature - PPSN XII - 12th International Conference, Taormina, Italy, September 1-5, 2012, Proceedings, Part II. 337–347.Recent developments in fitness landscape analysis include the study of Local Optima Networks (LON) and applications of the Elementary Landscapes theory. This paper represents a first step at combining these two tools to explore their ability to forecast the performance of search algorithms. We base our analysis on the Quadratic Assignment Problem (QAP) and conduct a large statistical study over 600 generated instances of different types. Our results reveal interesting links between the network measures, the autocorrelation measures and the performance of heuristic search algorithms.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Spanish Ministry of Science and Innovation and FEDER under contract TIN2011-28194. Andalusian Government under contract P07-TIC-03044. Swiss National Science Foundation for financial support under grant number 200021-124578

Parsing of Spoken Language under Time Constraints

Spoken language applications in natural dialogue settings place serious requirements on the choice of processing architecture. Especially under adverse phonetic and acoustic conditions parsing procedures have to be developed which do not only analyse the incoming speech in a time-synchroneous and incremental manner, but which are able to schedule their resources according to the varying conditions of the recognition process. Depending on the actual degree of local ambiguity the parser has to select among the available constraints in order to narrow down the search space with as little effort as possible. A parsing approach based on constraint satisfaction techniques is discussed. It provides important characteristics of the desired real-time behaviour and attempts to mimic some of the attention focussing capabilities of the human speech comprehension mechanism.Comment: 19 pages, LaTe

Artificial Intelligence Approaches to Medical Diagnosis

Work reported herein was conducted at the Artificial Intelligence Laboratory, a Massachusetts Institute of Technology research program supported in part by the Advanced Research Projects Agency of the Department of Defense and monitored by the Office of Naval Research under Contract Number N00014-70-A-0362-0005.The differential diagnosis of hematuria, blood in the urine, is studied from the point of view of identifying crucial structures and processes in medical diagnosis. The thesis attempts to fit the problem of medical diagnosis into the framework of other A.I. problems and paradigms and in particular explores the notions of pure search vs. heuristic methods, linearity and interaction, plausibility and the structure of hypotheses within the world of kidney disease.MIT Artificial Intelligence Laborator

Stateful Testing: Finding More Errors in Code and Contracts

Automated random testing has shown to be an effective approach to finding faults but still faces a major unsolved issue: how to generate test inputs diverse enough to find many faults and find them quickly. Stateful testing, the automated testing technique introduced in this article, generates new test cases that improve an existing test suite. The generated test cases are designed to violate the dynamically inferred contracts (invariants) characterizing the existing test suite. As a consequence, they are in a good position to detect new errors, and also to improve the accuracy of the inferred contracts by discovering those that are unsound. Experiments on 13 data structure classes totalling over 28,000 lines of code demonstrate the effectiveness of stateful testing in improving over the results of long sessions of random testing: stateful testing found 68.4% new errors and improved the accuracy of automatically inferred contracts to over 99%, with just a 7% time overhead.Comment: 11 pages, 3 figure

Computational experience with a branch-and-bound procedure for the resource-constrained project scheduling problem with generalized precedence relations.

In a previous paper (De Reyck and Herroelen, 1996a), we presented an optimal procedure for the resource-constrained project scheduling problem (RCPSP) with generalised precedence relations (further denoted as RCPSP-GPR) with the objective of minimizing the project makespan. The RCPSP-GPR extends the RCPSP to arbitrary minimal and maximal time lags between the starting and completion times of activities. The procedure is a depth-first branch -and-bound algorithm in which the nodes in the search tree represent the original project network extended with extra precedence relations, which resolve a resource conflict present in the project network of the parent node. Resource conflicts are resolved using the concept of minimal delaying alternatives, i.e. minimal sets of activities which, when delayed, release enough resources to resolve the conflict. Precedence- and resource-based lower bounds as well as dominance rules are used to fathom large portions of the search tree. In this paper we report new computational experience with the algorithm using a new RCPSP-GPR random problem generator developed by Schwindt (1995). A comparison with other computational results reported in the literature is included.Scheduling;

Tramp Ship Scheduling Problem with Berth Allocation Considerations and Time-dependent Constraints

This work presents a model for the Tramp Ship Scheduling problem including berth allocation considerations, motivated by a real case of a shipping company. The aim is to determine the travel schedule for each vessel considering multiple docking and multiple time windows at the berths. This work is innovative due to the consideration of both spatial and temporal attributes during the scheduling process. The resulting model is formulated as a mixed-integer linear programming problem, and a heuristic method to deal with multiple vessel schedules is also presented. Numerical experimentation is performed to highlight the benefits of the proposed approach and the applicability of the heuristic. Conclusions and recommendations for further research are provided.Comment: 16 pages, 3 figures, 5 tables, proceedings paper of Mexican International Conference on Artificial Intelligence (MICAI) 201

Project network models with discounted cash flows. A guided tour through recent developments.

The vast majority of the project scheduling methodologies presented in the literature have been developed with the objective of minimizing the project duration subject to precedence and other constraints. In doing so, the financial aspects of project management are largely ignored. Recent efforts have taken into account discounted cash flow and have focused on the maximalization of the net present value (npv) of the project as the more appropriate objective. In this paper we offer a guided tour through the important recent developments in the expanding field of research on deterministic and stochastic project network models with discounted cash flows. Subsequent to a close examination of the rationale behind the npv objective, we offer a taxonomy of the problems studied in the literature and critically review the major contributions. Proper attention is given to npv maximization models for the unconstrained scheduling problem with known cash flows, optimal and suboptimal scheduling procedures with various types of resource constraints, and the problem of determining both the timing and amount of payments.Scheduling; Models; Model; Discounted cash flow; Cash flow; Project scheduling; Project management; Management; Net present value; Value; Problems; Maximization; Optimal;