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28th Annual IEEE International Conference on Tools with Artificial Intelligence (ICTAI)

作者： Pereira, Leonardo T. Toledo, Claudio F. M. Univ Sao Paulo Inst Math & Comp Sci BR-13566590 Sao Carlos SP Brazil

This research uses Machine Learning (ML) techniques in order to aid search-based (SB) algorithms to improve level generation for physics-based puzzle games. These algorithms' performance are improved by reducing simulation time when the ML techniques are applied. Classification algorithms prevent levels with undesired traits to be evaluated during the simulation phase of the SB procedures. An Angry Birds clone is used for conducting the experiments and results report improvement using the combined approach against every SB algorithm by itself.

关键词： search-based algorithms machine learning procedural content generation classification video game

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Speeding up search-based algorithms for Level Generation in Physics-based Puzzle Games

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INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS 2017年第5期26卷

作者： Pereira, Leonardo T. Toledo, Claudio F. M. Univ Sao Paulo Inst Math & Comp Sci BR-13566590 Sao Carlos SP Brazil

关键词： search-based algorithms machine learning procedural content generation classification video game

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Low-time complexity budget-deadline constrained workflow scheduling on heterogeneous resources

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2016年 55卷 29-40页

作者： Arabnejad, Hamid Barbosa, Jorge G. Prodan, Radu Univ Porto Fac Engn Dept Engn Informat LIACC Rua Campo Alegre 823 P-4100 Oporto Portugal Univ Innsbruck Inst Comp Sci A-6020 Innsbruck Austria

The execution of scientific applications, under the utility computing model, is constrained to Quality of Service (QoS) parameters. Commonly, applications have time and cost constraints such that all tasks of an application need to be finished within a user-specified Deadline and Budget. Several algorithms have been proposed for multiple QoS workflow scheduling, but most of them use search-based strategies that generally have a high time complexity, making them less useful in realistic scenarios. In this paper, we present a heuristic scheduling algorithm with quadratic time complexity that considers two important constraints for QoS-based workflow scheduling, time and cost, named Deadline Budget Constrained Scheduling (DBCS). From the deadline and budget defined by the user, the DBCS algorithm finds a feasible solution that accomplishes both constraints with a success rate similar to other state-of-the-art search based algorithms in terms of the successful rate of feasible solutions, consuming in the worst case only approximately 4% of the time. The DBCS algorithm has a low-time complexity of O(n(2).p) for n tasks and p processors. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Quality of Service Grids Clouds List scheduling search-based algorithms

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Models and algorithms for workforce allocation and utilization

Models and algorithms for workforce allocation and utilizati...

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作者： Barlatt, Ada Yetunde University of Michigan

学位级别：Ph.D.

Workforce planning is an important process that: (1) enables organizations to determine the most efficient workforce composition, and (2) provides a foundation to recruit and/or reorganize the workforce to achieve organizational goals. An effective workforce plan has the right number of workers with the right skills for the right tasks at the right time. Unfortunately, simultaneously determining the workforce allocation - the number of workers with each skill set available during the horizon - and the workforce utilization - the sequence of tasks scheduled during the horizon to meet customer demand - is not a trivial task. In workforce planning problems one decision affects many others, resulting in many inter-connected, complicated constraints. Applying traditional techniques to solve workforce planning problems can lead to tremendous challenges. For example, the use of mathematical programming techniques can be hampered by non-linearities and weak linear programming relaxations. This dissertation presents new mathematical models and solution techniques to accurately model and efficiently solve workforce planning problems. The work in this dissertation is motivated by existing problems in the service and manufacturing industries. Computational results based on data from a major automotive manufacturer demonstrate how the models and algorithms developed provide high-quality, realistic workforce plans in reasonable run times. This research could be extended to address other workforce planning problems in the manufacturing and service industries. In addition, the algorithms and models created can be applied to other resource allocation and utilization problems.

关键词： Optimization Scheduling search-based algorithms Workforce Planning Integer Programming Thesis

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Optimalizace testování pomocí algoritmů prohledávání prostoru

Optimalizace testování pomocí algoritmů prohledávání ...

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作者： Starigazda, Michal Brno University of Technology

Testování vícevláknových programů je náročný proces kvůli velkému množství možných interakcí mezi vlákny, které je třeba otestovat. Technika vklád&... 详细信息

Testování vícevláknových programů je náročný proces kvůli velkému množství možných interakcí mezi vlákny, které je třeba otestovat. Technika vkládání šumu umožňuje zvýšit počet otestovaných proložení (interakcí) konkurenčních vláken generováním šumu. Tato práce optimalizuje techniky prohledávání prostoru v oblasti testování vícevláknových programů, a to s využitím deterministických heuristik použitých při aplikací genetických algoritmů na prostor míst v běhu programu, do kterých je možné umístit šum. V práci je navrženo několik nových heuristik vkládání šumu, které jsou deterministické, narozdíl od většiny současných heuristik pracujících s generátorem náhodných čísel. Motivací odstranění náhodnosti je informovanější prohledávání a získávání optimálnějších výsledků pomoci zvýšení stability výsledku poskytovaných novými heuristikami. Součástí práce je i základní sada testovacích programů, která bude použita k vyhodnocení výsledků nových heuristik vkládání šumu.

关键词： testovaní optimalizace testování algoritmy prohledávání prostoru metaheuristiky vkládaní šumu vícevláknové programy genetické algoritmy metriky pokrytí testing test optimization search-based algorithms metaheuristics noise injection multi-thr

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Numerical solution of fuzzy linear equations in engineering analysis

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INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING 1998年第3期43卷 391-408页

作者： Rao, SS Chen, L Purdue Univ Sch Mech Engn W Lafayette IN 47907 USA

A computational methodology is presented for the solution of simultaneous linear equations that arise in the analysis of engineering systems involving fuzzy input parameters In addition to a discussion on the existence of solution to the problem, the numerical solution to the fuzzy linear systems is defined and formalized. The framework of the proposed methodology consists of three major aspects involving (1) computerized selection of fuzziness, (2) implementation of fuzzy operations and (3) development and execution of a search-based algorithm. Two numerical examples are presented to illustrate the computational aspects of the proposed methodology. The present results are compared to those given by the combinatorial approach. (C) 1998 John Wiley & Sons, Ltd.

关键词： fuzzy analysis linear equations numerical solution fuzzy systems search-based algorithms

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Automated test case generation based on differential evolution with node branch archive

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COMPUTERS & INDUSTRIAL ENGINEERING 2021年 156卷

作者： Dai, Xiaohu Gong, Wenyin Gu, Qiong China Univ Geosci Sch Comp Sci Wuhan 430074 Peoples R China Hubei Univ Arts & Sci Sch Comp Engn Xiangyang 441053 Peoples R China

Automatic test case generation (ATCG) is the active research topic in software testing engineering, which can greatly reduce the cost of software testing. In automated test case generation for path coverage (ATCG-PC) problem, since the relationship between test cases and paths is unknown, there are many redundant test cases in the test case set to meet the path coverage criteria. In many previous studies on search-based algorithms for ATCG-PC, researchers have focused on improving the search-based algorithms itself or designing a more suitable fitness function according to the coverage criteria. However, the relationship between test cases and paths can help search-based algorithms cover more paths. The values of some specific test case dimensions change, and offspring individuals may cover different paths. Inspired by this, we proposed a node branch archive strategy, which can record the relationship between node branch direction and the value of test case variables, and cover more paths through this driven search-based algorithms. The experimental results show that compared with other state-of-the-art algorithms, the differential evolution with node branch archive (NBAr-DE) can significantly reduce the number of redundant test cases.

关键词： Automated test case generation search-based algorithms Differential evolution Path coverage Node branch archive

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A tandem white shark algorithm approach for optimizing drug-disease and drug-drug interactions in multimorbidity and polypharmacy

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BIOMEDICAL SIGNAL PROCESSING AND CONTROL 2024年 87卷

作者： Al Khatib, Sultan M. Al Balqa Appl Univ Prince Abdullah Bin Ghazi Fac Informat & Commun Te Dept Software Engn Al Salt 19117 Jordan

Minimizing Drug-disease and drug-drug Interactions in Polypharmacy and Multimorbidity (DIPM) is a challenging problem. The challenge is caused by the large number of similar medications that can be prescribed for each disease and the adverse reactions that may be experienced by the selected medication(s) for one or more of the diseases and medications identified. Therefore, it is a selection problem as to which medication should be prescribed to the patient for each disease while maintaining the least drug-disease and drug-drug interactions. This is an optimization problem, and to the best of our knowledge, it has never been addressed before using search-based algorithms. The aims of this study are to explore and find the best performance among the employed algorithms in providing optimal or near-optimal solutions to this problem, and then to fine -tune an optimization approach to DIPM. Four algorithms are consequently employed, which are: Dragonfly Algorithm (DA), Whale Optimization Algorithm (WOA), Genetic Algorithm (GA), and White Shark Optimization (WSO). To test the most suitable one among the algorithms, two synthetic datasets are used, representing simple and more complex problems. The results, considering only drug-disease interactions, show that GA is outperforming the others for a simple problem. However, WSO is found to outperform the others when the problem is more complex. The WSO is accordingly formed into a tandem approach, considering both drug-disease and drug-drug interactions for a real-world problem dataset. The approach indicates promising results with accuracy of (100%) for drug-drug interaction and (96.6%) for drug-disease interaction in (5.32) seconds.

关键词： Tandem White Shark Optimization approach Drug-disease interactions Drug-drug interactions Multimorbidity and polypharmacy search-based algorithms Dragonfly Algorithm Whale Optimization algorithms Genetic algorithms White Shark Optimization

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Numerical solution of fuzzy linear equations in engineering analysis

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INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING 1998年第5期42卷 829-846页

作者： Rao, SS Chen, L Purdue Univ Sch Mech Engn W Lafayette IN 47907 USA

A computational methodology is presented for the solution of simultaneous linear equations that arise in the analysis of engineering systems involving fuzzy input parameters. In addition to a discussion on the existence of solution to the problem, the numerical solution to the fuzzy linear systems is defined and formalized. The framework of the proposed methodology consists of three major aspects involving (1) computerized selection of fuzziness, (2) implementation of fuzzy operations and (3) development and execution of a search-based algorithm. Two numerical examples are presented to illustrate the computational aspects of the proposed methodology. The present results ate compared with those given by the combinatorial approach. (C) 1998 John Wiley & Sons, Ltd.

关键词： fuzzy analysis linear equations numerical solution fuzzy systems search-based algorithms

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