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30 Ergebnisse
Bereich: Suchergebnisse
Publikation Open-ended automatic programming through combinatorial evolution(Springer, 2021) Fix, Sebastian; Probst, Thomas; Ruggli, Oliver; Hanne, Thomas; Christen, Patrik; Abraham, Ajith; Gandhi, Niketa; Hanne, Thomas; Hong, Tzung-Pei; Rios, Tatiane Nogueira; Ding, Weiping04B - Beitrag KonferenzschriftPublikation A logistics serious game(2021) Pustulka, Elzbieta; Güler, Attila; Hanne, ThomasSwitzerland is a logistics hub which needs many trained professionals. As logistics does not have a strong public image, the profession does not attract enough young people. A logistics game could help recruit more candidates at the apprenticeship and university level and help in teaching. We have prototyped a logistics game and found out that it raises interest in logistics and successfully teaches about cargo ships. The game test showed that the game is visually appealing but the competitive aspect may interfere with learning.04B - Beitrag KonferenzschriftPublikation Gaussian guided self-adaptive wolf search algorithm(MDPI, 2018) Song, Qun; Fong, Simon; Deb, Suash; Hanne, ThomasNowadays, swarm intelligence algorithms are becoming increasingly popular for solving many optimization problems. The Wolf Search Algorithm (WSA) is a contemporary semi-swarm intelligence algorithm designed to solve complex optimization problems and demonstrated its capability especially for large-scale problems. However, it still inherits a common weakness for other swarm intelligence algorithms: that its performance is heavily dependent on the chosen values of the control parameters. In 2016, we published the Self-Adaptive Wolf Search Algorithm (SAWSA), which offers a simple solution to the adaption problem. As a very simple schema, the original SAWSA adaption is based on random guesses, which is unstable and naive. In this paper, based on the SAWSA, we investigate the WSA search behaviour more deeply. A new parameter-guided updater, the Gaussian-guided parameter control mechanism based on information entropy theory, is proposed as an enhancement of the SAWSA. The heuristic updating function is improved. Simulation experiments for the new method denoted as the Gaussian-Guided Self-Adaptive Wolf Search Algorithm (GSAWSA) validate the increased performance of the improved version of WSA in comparison to its standard version and other prevalent swarm algorithms.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Finding the best third-party logistics in the automobile industry(Hindawi, 2018) Yazdi, Amir Karbassi; Hanne, Thomas; Osorio Gómez, Juan Carlos; García Alcaraz, Jorge LuisGiven the current economic climate, many companies are considering outsourcing some activities to reduce costs and to focus on their core competency; thus, by adopting a competency-focused approach they enhance their chances to survive in a growing and competitive market. Third-Party Logistics (3PL) is a system that facilitates logistic activities. First, however, the organizations need to assess which companies are suitable for outsourcing. The aim of this paper is to depict a structural system for 3PL selection and validate it in real-world automobile companies. We use the Delphi method to determine criteria for 3PL selection and apply Evaluation by an Area-based Method for Ranking (EAMR) to prioritize the candidate alternatives. This method is used in combination with a Shannon Entropy based approach for determining the required weights. Computational analysis shows which criteria and companies have high priority, and based on that candidate alternatives for outsourcing are evaluated. The results suggest how automobile companies select 3PL companies and allocate their work to them.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Freelancing models for fostering innovation and problem solving in software startups: an empirical comparative study(MDPI, 2020) Gupta, Varun; Fernandez-Crehuet, Jose Maria; Gupta, Chetna; Hanne, ThomasContext: freelancers and startups could provide each other with promising opportunities that lead to mutual growth, by improving software development metrics, such as cost, time, and quality. Niche skills processed by freelancers could help startups reduce uncertainties associated with developments and markets, with the ability to quickly address market issues (and with higher quality). This requires the associations between freelancers and startup to be long-term, based on trust, and promising agreements driven by motivations (leading to the growth of both parties). Freelancers could help startups foster innovations and undertake software development tasks in better ways than conducted in-house, if they are selected using informed decision-making. Objectives: the paper has three objectives, (1) to explore the strategies of startups to outsource software development tasks to freelancers (termed as freelancing association strategies); (2) to identify challenges in such outsourcings; and (3) to identify the impacts of outsourcing tasks to freelancers on overall project metrics. The overall objective is to understand the strategies for involving freelancers in the software development process, throughout the startup lifecycle, and the associated challenges and the impacts that help to foster innovation (to maintain competitive advantages). Method: this paper performs empirical studies through case studies of three software startups located in Italy, France, and India, followed by a survey of 54 freelancers. The results are analyzed and compared in the identification of association models, issues, challenges, and reported results arising because of such associations. The case study results are validated using members checking with the research participants, which shows a higher level of result agreements. Results: the results indicate that the freelancer association strategy is task based, panel based, or a hybrid. The associations are constrained by issues such as deciding pricing, setting deadlines, difficulty in getting good freelancers, quality issues with software artefacts, and efforts to access freelancer work submissions for reward. The associations have a positive impact on software development if there is availability of good freelancers (which lasts long for various tasks). The paper finally provides a freelancing model framework and recommends activities that could result in making the situation beneficial to both parties, and streamline such associations. Fostering innovation in startups is, thus, a trade-off situation, which is limited and supported by many conflicting parameters.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Evaluating the performance of Colombian banks by hybrid multicriteria decision making methods(Vilnius Gediminas Technical University, 2020) Yazdi, Amir Karbassi; Hanne, Thomas; Osorio Gómez, Juan CarlosThe aim of the study in this paper is to show how the performance of banks can be evaluated by ranking them based on Balanced Scorecard (BSC) and Multicriteria Decision Making (MCDM) methods. Nowadays, assessing the performance of companies is a vital work for finding their weaknesses and strengths. The banking sector is an important area in the service sector. Many people want to know which bank performs best when entrusting their money to them. For assessing the performance of banks, BSC can be used. This method helps to translate strategic issues to meaningful insights for the respective financial institutions. After that, the banks will be ranked based on performance indicators by the Weighted Aggregated Sum Product Assessment (WASPAS) method. Because this method is based on a decision matrix, weights are required. To find such weights, the Step-wise Weight Assessment Ratio Analysis (SWARA) method is applied. The results show that the International Bank of Colombia has a much better performance than other Colombian banks. Besides, further insights regarding the evaluation process based on BSC, SWARA, and WASPAS are obtained.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Building a technology recommender system using web crawling and natural language processing technology(MDPI, 2022) Campos Macias-Hammel, Nathalie; Düggelin, Wilhelm; Ruf, Yesim; Hanne, ThomasFinding, retrieving, and processing information on technology from the Internet can be a tedious task. This article investigates if technological concepts such as web crawling and natural language processing are suitable means for knowledge discovery from unstructured information and the development of a technology recommender system by developing a prototype of such a system. It also analyzes how well the resulting prototype performs in regard to effectivity and efficiency. The research strategy based on design science research consists of four stages: (1) Awareness generation; (2) suggestion of a solution considering the information retrieval process; (3) development of an artefact in the form of a Python computer program; and (4) evaluation of the prototype within the scope of a comparative experiment. The evaluation yields that the prototype is highly efficient in retrieving basic and rather random extractive text summaries from websites that include the desired search terms. However, the effectivity, measured by the quality of results is unsatisfactory due to the aforementioned random arrangement of extracted sentences within the resulting summaries. It is found that natural language processing and web crawling are indeed suitable technologies for such a program whilst the use of additional technology/concepts would add significant value for a potential user. Several areas for incremental improvement of the prototype are identified.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Effects of noisy multiobjective test functions applied to evolutionary optimization algorithms(Engineering and Technology Publishing, 2020) Ryter, Remo; Hanne, Thomas; Dornberger, RolfIn this paper we study the effects of noise in multiobjective optimization problems. We consider a test function, which may be affected by noise with different strength and frequency of occurrence. To simplify the analysis, the noise is applied to only one of the objective functions, i.e. one of the objective functions is affected by additional random influences. Three different evolutionary algorithms for multiobjective problems are analyzed in this way: the Covariance Matrix Adaption Evolution Strategy (CMA-ES), the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), and the Particle Swarm Optimization (PSO). The results are presented and analyzed with respect to the resulting Pareto fronts and with respect to the distribution of variable values during the algorithm run. It can be observed that all three algorithms are basically able to derive suitable results. However, only PSO leads to a sparse Pareto front in case of noisy and non-noisy situations while CMA and NSGA-II perform similarly well. In some situations for NSGA-II and more clearly for CMA-ES specific patterns for the variable values (denoted as striae in this paper) can be observed which appear to be partly caused by the noise.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Robotic path planning by Q learning and a performance comparison with classical path finding algorithms(Engineering and Technology, 2022) Chintala, Phalgun Chowdhary; Dornberger, Rolf; Hanne, ThomasQ Learning is a form of reinforcement learning for path finding problems that does not require a model of the environment. It allows the agent to explore the given environment and the learning is achieved by maximizing the rewards for the set of actions it takes. In the recent times, Q Learning approaches have proven to be successful in various applications ranging from navigation systems to video games. This paper proposes a Q learning based method that supports path planning for robots. The paper also discusses the choice of parameter values and suggests optimized parameters when using such a method. The performance of the most popular path finding algorithms such as A* and Dijkstra algorithm have been compared to the Q learning approach and were able to outperform Q learning with respect to computation time and resulting path length.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Optimization of artificial landscapes with a hybridized firefly algorithm(Engineering and Technology Publishing, 2022) Saner, Kevin; Smith, Kyle; Hanne, Thomas; Dornberger, RolfThis paper shows how the metaheuristic Firefly Algorithm (FA) can be enhanced by hybridization with a genetic algorithm to achieve better results for optimization problems. The authors examine which configuration of the hybridized FA performs best during a number of computational tests. The performance of the hybrid FA is compared with that of the regular FA in solving test functions for single-objective optimization problems in two and n-dimensional spaces. The key findings are that more complex optimization problems benefit from the hybrid FA because it outperforms the basic FA. In addition, some useful parameters settings for the suggested algorithm are determined.01A - Beitrag in wissenschaftlicher Zeitschrift
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