Telesko, Rainer
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Determination of weights for multiobjective combinatorial optimization in incident management with an evolutionary algorithm
Incident management in railway operations includes dealing with complex and multiobjective planning problems with numerous constraints, usually with incomplete information and under time pressure. An incident should be resolved quickly with minor deviations from the original plans and at acceptable costs. The problem formulation usually includes multiple objectives relevant to a railway company and the employees involved in controlling operations. Still, there is little established knowledge and agreement regarding the relative importance of objectives such as expressed by weights. Due to the difficulties in assessing weights in a multiobjective context directly involving decision makers, we elaborate on the autoconfiguration of weighted fitness functions based on nine objectives used in a related Integer Linear Programming (ILP) problem. Our approach proposes an evolutionary algorithm and tests it on real-world railway incident management data. The proposed method outperforms the baseline, where weights are equally distributed. Thus, the algorithm shows the capability to learn weights in future applications based on the priorities of employees solving railway incidents which is not yet possible due to an insufficient availability of real-life data from incident management. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10339298&tag=1
Requirements engineering in software startups: a systematic mapping study
Startups have high failure rates due to their inability to attain a sufficient product/market fit, i.e., delivering a solution that best matches the user needs in the market. Requirement engineering is the activity that could help startup teams identify the value proposition that provides high value to the users and continuously innovate it. The objective of the study is to analyse the state of art of the requirement engineering research in the context of startups, as available in the literature. The analysis of the research area highlights the research trends to achieve two things i.e., (a) predict how much support the startups can get from the literature for enhancing their success rates and (b) identify the research gaps to motivate researchers to conduct future research that could be adoptable in startup contexts. Systematic mapping is conducted on studies extracted from the four bibliographic databases (IEEExplore, ACM, Springerlink and ScienceDirect) and studies extracted by using a forward snowballing approach. Individual studies are coded to yield the classification scheme. Formulated schemes and those already available in literature, were populated with information extracted from the abstracts of the studies. The research is mostly focused on generic requirement engineering and product validation activities. The research is conducted mostly as evaluations (empirical studies) with the outcome of providing theory to the research community. Major underlying motivation of the research is to attain the product/market fit. However, research studies focusing on requirement documentation, prioritization and elicitation are losing focus from 2017, 2018 and 2019, respectively. The literature lacks the studies that reports research solutions which are validated in laboratory settings or in real contexts, experience reports, opinion papers and philosophical papers. The positive side of the finding is that the number of requirement engineering research studies in a startup context have increased in the past five years. At this instant, unfortunately the literature has limited ability to support startups by providing solutions (for instance, research solutions, evidence to support decision makings, best practices, experiences etc.) that are adoptable in their real context. Uniform focus of the researchers across all sub-activities of requirement engineering is required with effort distributed across different research types that supports startups, not only by providing validated solutions but experience reports, opinions, new conceptual frameworks and empirical evidence that can aid their decision making.
Derivation of an agile method construction set to optimize the software development process
Today, IT and especially the development of customer-focused software, has become one of the most important elements for a company to remain competitive. The primary purpose of this paper is to determine whether it is possible to improve the agile development of a company by adjusting its software development process in terms of cultural, technical and managerial dimensions. Based on a literature analysis and practical experience in the company, different influencing factors and parameters, which affect the value creation throughout the software development process of a company were derived and clustered. Out of these clusters, a framework (Agile Method Construction Set) based on a Microsoft® Excel questionnaire was created in order to analyze and identify optimization potential in the development process of a company. This construction set was adapted to meet the requirements of the development department of a large Swiss insurance company in order to validate and test the framework with real data.
Gut gereift. Management von Geschäftsprozessen
Geschäftsprozessmanagement (GPM) ist ein komplexes Thema und nicht immer ist es möglich, den Verantwortlichen den konkreten Nutzen sofort begreiflich zu machen. Reifegradmodelle können als Mittel zur Standortund Zielbestimmung eingesetzt werden. Dabei kann zum Beispiel der eigene Entwicklungsstand mit ähnlichen Unternehmen verglichen werden. Mithilfe eines Reifegradmodells können also der aktuelle Entwicklungsstand eines Unternehmens erhoben, das Optimierungspotenzial ermittelt und ein entsprechendes Massnahmenpaket definiert werden.
A new approach for teaching programming: model-based agile programming (MBAD)
Designing courses for introductory programming courses with a heterogeneous audience (business and IT background as well) is a challenging task. In an internal project of the School of Business at the FHNW University of Applied Sciences and Arts Northwestern Switzerland (FHNW) a group of lecturers developed a concept entitled “Model-based agile development” (MBAD) which supports the learning of elementary programming concepts in an agile environment and builds the basis for advanced courses. MBAD will be used as a basic learning module for various Bachelor programs at the FHNW.
Fostering product innovations in software startups through freelancer supported requirement engineering
This research paper explores the involvement of freelancers in requirement engineering activities to continuously innovating the value propositions and utilizing their expertise in various requirement engineering tasks. This paper reports the case study conducted with the startups that involve freelancers for the requirement engineering activities. The findings are then compared with the literature to explore the freelancer supported requirement engineering domain. Results indicate that the freelancers could help innovate value proposition by providing different perspectives of the global segments and also expertise in executing requirement engineering activities. The freelancers have varying levels of involvement in requirement engineering activities depending on on startup contexts and is highly challenged by various inhibitors. The inhibitors include difficulty to select freelancers optimally, ensuring their long term association for continuous rework arising because of continuous learnings in the market, building trust, mechanism to integrate their perspective, establishing communication, negotiations and strategic pricings. However, there is a need to optimally establish the freelancer involvement from beginning of the startup life cycle with a promise for long term benefits in exchange for their trustworthy and accurate perspectives, which is harder to get by involving crowds of customers due to resource limitations. Further research is required to investigate how freelancers could represent the samples of globally distributed customer segments as input source of information on one side and on another side become startup team representatives to establish direct interactions with global customer segments.
Gig work business process improvement
We collaborate with a gig work platform company (GPC) in Switzerland. The project aims to improve the business by influencing process management within the GPC, providing automated matching of jobs to workers, improving worker acquisition and worker commitment, and particularly focusing on the prevention of no shows. One expects to achieve financial, organizational and efficiency gains. As research tools we use a combination of text mining and sentiment analysis, Business Process Modeling and Notation (BPMN), interviews with workers and employers, and the design of sociotechnical improvements to the process, including platform improvements and prototypes. Here, we focus on the successful combination of BPMN modelling with sentiment analysis in the identification of problems and generation of ideas for future modifications to the business processes.
Implementing the AoL standard for the WI and BIT curricula in AACSB – Lessons learned at the FHNW
Before 2014, the quality management process in all our programs has been rather informally and individually organized. In 2014, the management of the School of Business at the FHNW decided to set up a strategic project to achieve the AACSB accreditation to sustainably secure the role among the best business schools. Among other standards, AACSB deals with Assurance of Learning (AoL, standard 5 in the 2020 standards) with the clear goal formulated as "The school uses well-documented, systematic processes for determining and revising degree program learning goals; designing, delivering, and improving degree program curricula to achieve learning goals; and demonstrating that degree program learning goals have been met." The AoL process has been established step by step since 2015 and provided us with a guideline to check the mission-reference of our program goals and learning objectives and to continuously develop the program quality on a common database. This paper describes the implementation of AoL using the four steps "Determining Degree Program Learning Goals", "Measure", "Results" and "Closing the Loop" for the bachelor programs WI (in German "Wirtschaftsinformatik") and BIT (Business Information Technology). As examples, measurements and improvements for various modules (spanning from supply chain to the computer science domain) are discussed, underpinning the clear and significant progress in the management of curricula and in the monitoring of our study programs’ effectiveness regarding student learning. Finally, we outline selected AoL initiatives at other universities and show how we can benefit from them to successfully enhance our project.
Combining symbolic and sub-symbolic AI in the context of education and learning
Abstraction abilities are key to successfully mastering the Business Information Technology Programme (BIT) at the FHNW (Fachhochschule Nordwestschweiz). Object-Orientation (OO) is one example - which extensively requires analytical capabilities. For testing the OO-related capabilities a questionnaire (OO SET) for prospective and 1st year students was developed based on the Blackjack scenario. Our main target of the OO SET is to identify clusters of students which are likely to fail in the OO-related modules without a substantial amount of training. For the interpretation of the data the Kohonen Feature Map (KFM) is used which is nowadays very popular for data mining and exploratory data analysis. However, like all sub-symbolic approaches the KFM lacks to interpret and explain its results. Therefore, we plan to add - based on existing algorithms - a “postprocessing” component which generates propositional rules for the clusters and helps to improve quality management in the admission and teaching process. With such an approach we synergistically integrate symbolic and sub-symbolic artificial intelligence by building a bridge between machine learning and knowledge engineering.
Bestmögliche Verzahnung
ABLAUFOPTIMIERUNG: Ein gutes Prozessmanagement sorgt dafür, dass die unzähligen Rädchen eines Unternehmens reibungslos ineinander greifen. Schon heute ist es in vielen Betrieben ein wesentlicher Bestandteil der Unternehmensführung geworden – und wird dies künftig noch in viel stärkerem Ausmass sein.