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  • 1.
    Allahviranloo, Tofigh
    et al.
    Azad University, Teheran, Iran.
    Arjan, Skuka
    Izmir University, Izmir, Turkey.
    Tahvili, Sahar
    Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics.
    On the global solution of a fuzzy linear system2014In: Journal of Fuzzy Set Valued Analysis, ISSN 2193-4169, article id jfsva-00190Article in journal (Other academic)
    Abstract [en]

    The global solution of a fuzzy linear system contains the crisp vector solution of a real linear system. So discussion about the global solution of a  fuzzy linear system  with a fuzzy number vector  in the right hand side and crisp a coefficient matrix  is considered. The advantage of the paper is developing a new algorithm to find the solution of such system by considering a global solution based upon the concept of a convex fuzzy numbers. At first the existence and uniqueness of the solution are introduced and then the related theorems and properties about the solution are proved in details. Finally the method is illustrated by solving some numerical examples.

  • 2.
    Saadatmand, Mehrdad
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Swedish Institute of Computer Science (SICS), Vasteras, Sweden.
    Tahvili, Sahar
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    A Fuzzy Decision Support Approach for Model-Based Tradeoff Analysis of Non-Functional Requirements2015In: 12th International Conference on Information Technology: New Generations ITNG 2015, Las Vegas, United States, 2015, Vol. Article number 7113458, p. 112-121Conference paper (Refereed)
    Abstract [en]

    One of the main challenges in addressing Non-Functional Requirements (NFRs) in designing systems is to take into account their interdependencies and mutual impacts. For this reason, they cannot be considered in isolation and a careful balance and tradeoff among them should be established. This makes it a difficult task to select design decisions and features that lead to the satisfaction of all different NFRs in the system, which becomes even more difficult when the complexity of a system grows. In this paper, we introduce an approach based on fuzzy logic and decision support systems that helps to identify different design alternatives that lead to higher overall satisfaction of NFRs in the system. This is achieved by constructing a model of the NFRs and then performing analysis on the model. To build the model, we use a modified version of the NFR UML profile which we have introduced in our previous works, and using model transformation techniques we automate the analysis of the model.

  • 3.
    Tahvili, Sahar
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    A Decision Support System for Integration Test Selection2016Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Software testing generally suffers from time and budget limitations. Indiscriminately executing all available test cases leads to sub-optimal exploitation of testing resources. Selecting too few test cases for execution on the other hand might leave a large number of faults undiscovered. Test case selection and prioritization techniques can lead to more efficient usage of testing resources and also early detection of faults. Test case selection addresses the problem of selecting a subset of an existing set of test cases, typically by discarding test cases that do not add any value in improving the quality of the software under test. Test case prioritization schedules test cases for execution in an order to increase their effectiveness at achieving some performance goals such as: earlier fault detection, optimal allocation of testing resources and reducing overall testing effort. In practice, prioritized selection of test cases requires the evaluation of different test case criteria, and therefore, this problem can be formulated as a multi-criteria decision making problem. As the number of decision criteria grows, application of a systematic decision making solution becomes a necessity. In this thesis, we propose a tool-supported framework using a decision support system, for prioritizing and selecting integration test cases in embedded system development. The framework provides a complete loop for selecting the best candidate test case for execution based on a finite set of criteria. The results of multiple case studies, done on a train control management subsystem from Bombardier Transportation AB in Sweden, demonstrate how our approach helps to select test cases in a systematic way. This can lead to early detection of faults while respecting various criteria. Also, we have evaluated a customized return on investment metric to quantify the economic benefits in optimizing system integration testing using our framework.

  • 4.
    Tahvili, Sahar
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. SICS Swedish ICT, Sweden.
    An Online Decision Support Framework for Integration Test Selection and Prioritization (Doctoral Symposium)2016In: The International Symposium on Software Testing and Analysis ISSTA'16, 2016Conference paper (Refereed)
    Abstract [en]

    Test case prioritization and selection techniques can lead to early detection of faults and can also enable more efficient usage of testing resources. The available methods of test case selection and prioritization suffer from one or several weaknesses. For example, most of them are only applicable at unit level and do not consider the increasing complexity when subsystems get integrated, especially in the context of embedded system development. Furthermore, the existing methods do not take into account results of current test execution to identify and optimize order for rest of the current execution (i.e., they are not online). In this paper, we propose a tool-supported framework, as an online decision support system (DSF), for prioritizing and selecting integration test cases for embedded system development. DSF provides a complete loop for selecting the best candidate test case for execution based on a finite set of criteria. The results of multiple case studies, done on a train control management subsystem from Bombardier Transportation (BT) in Sweden, demonstrate how our approach helps in a systematic way to select test cases such that it can lead to early detection of faults while respecting various criteria. We are also working towards proposing a customized return on investment (ROI) metric to quantify the economic benefits in optimizing system integration testing using our proposed DSF.

  • 5.
    Tahvili, Sahar
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. RISE SICS Västerås.
    Multi-Criteria Optimization of System Integration Testing2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Optimizing software testing process has received much attention over the last few decades. Test optimization is typically seen as a multi-criteria decision making problem. One aspect of test optimization involves test selection, prioritization and execution scheduling. Having an efficient test process can result in the satisfaction of many objectives such as cost and time minimization. It can also lead to on-time delivery and a better quality of the final software product. To achieve the goal of test efficiency, a set of criteria, having an impact on the test cases, need to be identified. The analysis of several industrial case studies and also state of the art in this thesis, indicate that the dependency between integration test cases is one such criterion, with a direct impact on the test execution results. Other criteria of interest include requirement coverage and test execution time. In this doctoral thesis, we introduce, apply and evaluate a set of approaches and tools for test execution optimization at industrial integration testing level in embedded software development. Furthermore, ESPRET (Estimation and Prediction of Execution Time) and sOrTES (Stochastic Optimizing of Test Case Scheduling) are our proposed supportive tools for predicting the execution time and the scheduling of manual integration test cases, respectively. All proposed methods and tools in this thesis, have been evaluated at industrial testing projects at Bombardier Transportation (BT) in Sweden. As a result of the scientific contributions made in this doctoral thesis, employing the proposed approaches has led to an improvement in terms of reducing redundant test execution failures of up to 40% with respect to the current test execution approach at BT. Moreover, an increase in the requirements coverage of up to 9.6% is observed at BT. In summary, the application of the proposed approaches in this doctoral thesis has shown to give considerable gains by optimizing test schedules in system integration testing of embedded software development.

  • 6.
    Tahvili, Sahar
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. RISE SICS Västerås, Sweden.
    Afzal, Wasif
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Saadatmand, Mehrdad
    RISE SICS Västerås, Sweden.
    Bohlin, Markus
    RISE SICS Västerås, Sweden.
    Hasan Ameerjan, Sharvathul
    ESPRET: A Tool for Execution Time Estimation of Manual Test Cases2018In: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 146, p. 26-41Article in journal (Refereed)
    Abstract [en]

    Manual testing is still a predominant and an important approach for validation of computer systems, particularly in certain domains such as safetycritical systems. Knowing the execution time of test cases is important to perform test scheduling, prioritization and progress monitoring. In this work, we present, apply and evaluate ESPRET (EStimation and PRediction of Execution Time) as our tool for estimating and predicting the execution time of manual test cases based on their test specifications. Our approach works by extracting timing information for various steps in manual test specifcation. This information is then used to estimate the maximum time for test steps that have not previously been executed, but for which textual specifications exist. As part of our approach, natural language parsing of the specifications is performed to identify word combinations to check whether existing timing information on various test steps is already available or not. Since executing test cases on the several machines may take different time, we predict the actual execution time for test cases by a set of regression models. Finally, an empirical evaluation of the approach and tool has been performed on a railway use case at Bombardier Transportation (BT) in Sweden.

  • 7.
    Tahvili, Sahar
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Afzal, Wasif
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Saadatmand, Mehrdad
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Bohlin, Markus
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Sundmark, Daniel
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Larsson, Stig
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Towards Earlier Fault Detection by Value-Driven Prioritization of Test Cases Using Fuzzy TOPSIS2016In: Information Technology: New Generations, vol. 440, Las Vegas, United States, 2016, p. 745-759Conference paper (Refereed)
    Abstract [en]

    In industrial software testing, development projects typically set up and maintain test suites containing large numbers of test cases. Executing a large number of test cases can be expensive in terms of effort and wall-clock time. Moreover, indiscriminate execution of all available test cases typically lead to sub-optimal use of testing resources. On the other hand, selecting too few test cases for execution might leave a large number of faults undiscovered. Limiting factors such as allocated budget and time constraints for testing further emphasizes the importance of test case prioritization in order to identify test cases that enable earlier detection of faults while respecting such constraints. In this paper, we propose a multi-criteria decision making approach for prioritizing test cases in order to detect faults earlier. This is achieved by applying the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) decision making technique combined with fuzzy principles. Our solution is based on important criteria such as fault detection probability, execution time, complexity, and other test case properties. By applying the approach on a train control management subsystem from Bombardier Transportation in Sweden, we demonstrate how it helps, in a systematic way, to identify test cases that can lead to early detection of faults while respecting various criteria.

  • 8.
    Tahvili, Sahar
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Bohlin, Markus
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Test Case Prioritization Using Multi Criteria Decision Making Methods2016In: Orbit: medlemsblad for Dansk Selskab for Operationsanalyse og Svenska Op, ISSN 1601-8893, Vol. 26, p. 9-11Article, review/survey (Refereed)
    Abstract [en]

    The lack of a systematic approach to decision making might leads to a non-optimal usage of resources. Nowadays, the real world decision making problems are multiple criteria, complex, large scale and generally consist of uncertainty and vagueness. Multiple-criteria decision making (MCDM) is a subset of operations research and is divided into Multi-Objective Decision Making (MODM) and Multi-Attribute Decision Making (MADM). The principal objective of the present article is proposing a systematic multi-criteria design making approach in the area of software testing that will be exemplified by an industrial example.

  • 9.
    Tahvili, Sahar
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Bohlin, Markus
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Saadatmand, Mehrdad
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Larsson, Stig
    SICS, Sweden.
    Afzal, Wasif
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Sundmark, Daniel
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Cost-Benefit Analysis of Using Dependency Knowledge at Integration Testing2016In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, Vol. 10027, p. 268-284Conference paper (Refereed)
    Abstract [en]

    In software system development, testing can take considerable time and resources, and there are numerous examples in the literature of how to improve the testing process. In particular, methods for selection and prioritization of test cases can play a critical role in efficient use of testing resources. This paper focuses on the problem of selection and ordering of integration-level test cases. Integration testing is performed to evaluate the correctness of several units in composition. Further, for reasons of both effectiveness and safety, many embedded systems are still tested manually. To this end, we propose a process, supported by an online decision support system, for ordering and selection of test cases based on the test result of previously executed test cases. To analyze the economic efficiency of such a system, a customized return on investment (ROI) metric tailored for system integration testing is introduced. Using data collected from the development process of a large-scale safety-critical embedded system, we perform Monte Carlo simulations to evaluate the expected ROI of three variants of the proposed new process. The results show that our proposed decision support system is beneficial in terms of ROI at system integration testing and thus qualifies as an important element in improving the integration testing process.

  • 10.
    Tahvili, Sahar
    et al.
    RISE SICS Västerås.
    Hatvani, Leo
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Felderer, Michael
    University of Innsbruck Innsbruck, Austria.
    Afzal, Wasif
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Bohlin, Markus
    RISE SICS Västerås AB , Västerås , Sweden.
    Automated Functional Dependency Detection Between Test Cases Using Text Semantic Similarity2019In: 2019 IEEE International Conference On Artificial Intelligence Testing (AITest), 2019, p. 19-26, article id 8718215Conference paper (Other academic)
    Abstract [en]

    Knowing about dependencies and similarities between test cases is beneficial for prioritizing them for cost-effective test execution. This holds especially true for the time consuming, manual execution of integration test cases written in natural language. Test case dependencies are typically derived from requirements and design artifacts. However, such artifacts are not always available, and the derivation process can be very time-consuming. In this paper, we propose, apply and evaluate a novel approach that derives test cases' similarities and functional dependencies directly from the test specification documents written in natural language, without requiring any other data source. Our approach uses an implementation of Doc2Vec algorithm to detect text-semantic similarities between test cases and then groups them using two clustering algorithms HDBSCAN and FCM. The correlation between test case text-semantic similarities and their functional dependencies is evaluated in the context of an on-board train control system from Bombardier Transportation AB in Sweden. For this system, the dependencies between the test cases were previously derived and are compared to the results our approach. The results show that of the two evaluated clustering algorithms, HDBSCAN has better performance than FCM or a dummy classifier. The classification methods' results are of reasonable quality and especially useful from an industrial point of view. Finally, performing a random undersampling approach to correct the imbalanced data distribution results in an F1 Score of up to 75% when applying the HDBSCAN clustering algorithm.

  • 11.
    Tahvili, Sahar
    et al.
    RISE, SICS, Västerås, Sweden.
    Hatvani, Leo
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Felderer, Michael
    University of Innsbruck, Austria, Sweden.
    Afzal, Wasif
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Saadatmand, Mehrdad
    RISE, SICS, Västerås, Sweden.
    Bohlin, Markus
    RISE, SICS, Västerås, Sweden.
    Cluster-Based Test Scheduling Strategies Using Semantic Relationships between Test Specifications2018In: 5th International Workshop on Requirements Engineering and Testing RET'18, 2018, Vol. F137811, p. 1-4Conference paper (Refereed)
    Abstract [en]

    One of the challenging issues in improving the test efficiency is that of achieving a balance between testing goals and testing resources. Test execution scheduling is one way of saving time and budget, where a set of test cases are grouped and tested at the same time. To have an optimal test execution schedule, all related information of a test case (e.g. execution time, functionality to be tested, dependency and similarity with other test cases) need to be analyzed. Test scheduling problem becomes more complicated at high-level testing, such as integration testing and especially in manual testing procedure. Test specifications at high-level are generally written in natural text by humans and usually contain ambiguity and uncertainty. Therefore, analyzing a test specification demands a strong learning algorithm. In this position paper, we propose a natural language processing (NLP) based approach that, given test specifications at the integration level, allows automatic detection of test cases’ semantic dependencies. The proposed approach utilizes the Doc2Vec algorithm and converts each test case into a vector in n-dimensional space. These vectors are then grouped using the HDBSCAN clustering algorithm into semantic clusters. Finally, a set of cluster-based test scheduling strategies are proposed for execution. The proposed approach has been applied in a sub-system from the railway domain by analyzing an ongoing testing project at Bombardier Transportation AB, Sweden.

  • 12.
    Tahvili, Sahar
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. RISE SICS Västerås.
    Pimentel, Rita
    Afzal, Wasif
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Ahlberg, Marcus
    Fornander, Eric
    Bohlin, Markus
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    sOrTES: A Supportive Tool forStochastic Scheduling of ManualIntegration Test CasesManuscript (preprint) (Other academic)
  • 13.
    Tahvili, Sahar
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. SICS Swedish ICT Västerås AB, Sweden.
    Saadatmand, Mehrdad
    SICS Swedish ICT Västerås AB, Sweden.
    Bohlin, Markus
    SICS Swedish ICT Västerås AB, Sweden.
    Multi-Criteria Test Case Prioritization Using Fuzzy Analytic Hierarchy Process2015In: ICSEA 2015: The Tenth International Conference on Software Engineering Advances, 2015, p. 290-296Conference paper (Refereed)
    Abstract [en]

    One of the key challenges in software testing today is prioritizing and evaluating test cases. The decision of which test cases to design, select and execute first is of great importance, in particular considering that testing is often done late in the implementation process, and therefore needs to be done within tight resource constraints on time and budget. In practice, prioritized selection of test cases requires the evaluation of different test case criteria, and therefore, test case prioritization can be formulated as a multi-criteria decision making problem. As the number of decision criteria grows, application of a systematic decision making solution becomes a necessity. In this paper we propose an approach for prioritized selection of test cases by using the Analytic Hierarchy Process (AHP) technique. To improve the practicality of the approach in real world scenarios, we apply AHP in fuzzy environment so that criteria values can be specified using fuzzy variables than requiring precise quantified values. One of the advantages of the decision making process it that the defined criteria with the biggest and most critical role in priority ranking of test cases is identified. We have applied our approach on an example case in which several test cases for testing non-functional requirements in a systems are defined.

  • 14.
    Tahvili, Sahar
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Saadatmand, Mehrdad
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Bohlin, Markus
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Afzal, Wasif
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Hasan Ameerjan, Sharvathul
    Towards Execution Time Prediction for Test Cases from Test Specification2017In: 2017 43RD EUROMICRO CONFERENCE ON SOFTWARE ENGINEERING AND ADVANCED APPLICATIONS (SEAA), Vienna, Austria, 2017, p. 421-425Conference paper (Refereed)
    Abstract [en]

    Knowing the execution time of test cases is important to perform test scheduling, prioritization and progress monitoring. This short paper presents a novel approach for predicting the execution time of test cases based on test specifications and available historical data on previously executed test cases. Our approach works by extracting timing information (measured and maximum execution time) for various steps in manual test cases. This information is then used to estimate the maximum time for test steps that have not previously been executed, but for which textual specifications exist. As part of our approach natural language parsing of the specifications is performed to identify word combinations to check whether existing timing information on various test activities already exists or not. Finally, linear regression is used to predict the actual execution time for test cases. A proof-of-concept use-case at Bombardier transportation serves to evaluate the proposed approach.

  • 15.
    Tahvili, Sahar
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. IS (Embedded Systems).
    Saadatmand, Mehrdad
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. IS (Embedded Systems).
    Larsson, Stig
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. ww.sics.se.
    Afzal, Wasif
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. IS (Embedded Systems).
    Bohlin, Markus
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. IS (Embedded Systems).
    Sundmark, Daniel
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. IS (Embedded Systems).
    Dynamic Integration Test Selection Based on Test Case Dependencies2016In: 2016 IEEE NINTH INTERNATIONAL CONFERENCE ON SOFTWARE TESTING, VERIFICATION AND VALIDATION WORKSHOPS (ICSTW), Chicago, United States, 2016, p. 277-286Conference paper (Refereed)
    Abstract [en]

    Prioritization, selection and minimization of test cases are well-known problems in software testing. Test case prioritization deals with the problem of ordering an existing set of test cases, typically with respect to the estimated likelihood of detecting faults. Test case selection addresses the problem of selecting a subset of an existing set of test cases, typically by discarding test cases that do not add any value in improving the quality of the software under test. Most existing approaches for test case prioritization and selection suffer from one or several drawbacks. For example, they to a large extent utilize static analysis of code for that purpose, making them unfit for higher levels of testing such as integration testing. Moreover, they do not exploit the possibility of dynamically changing the prioritization or selection of test cases based on the execution results of prior test cases. Such dynamic analysis allows for discarding test cases that do not need to be executed and are thus redundant. This paper proposes a generic method for prioritization and selection of test cases in integration testing that addresses the above issues. We also present the results of an industrial case study where initial evidence suggests the potential usefulness of our approach in testing a safety-critical train control management subsystem.

  • 16.
    Tahvili, Sahar
    et al.
    Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics.
    Österberg, Jonas
    Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics.
    Silvestrov, Sergei
    Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics.
    Strategic maintenance planning by fuzzy AHP and Markov Decision Processes2015In: ASMDA 2015 Proceedings: 16th Applied Stochastic Models and Data Analysis International Conference with 4th Demographics 2015 Workshop, ISAST: International Society for the Advancement of Science and Technology , 2015, p. 991-1004Conference paper (Refereed)
    Abstract [en]

    The work of engineering and business professionals includes making a series of decisions and optimizations. Real world decision making problems faced by decision makers (DM) involve multiple, usually conflicting, criteria. These multicriteria decision making problems (MCDM) are usually complicated and large in scale. In strategic Maintenance planning, choices are made on where to focus time and effort, where to spend money. We consider a framework for strategic maintenance planning in a modern maintenance driven organization. Our focus is on a multi-stage framework in which the planning is divided into two stages, identifying an optimal set of possible actions and finding the optimal decision policy for these actions for each point in time as a function of the stochastically evolving system state. To this respect we consider the MCDM method of AHP (Analytical hierarchical programming) in a fuzzy environment, and Markov decision processes (MDP).

  • 17.
    Tahvili, Sahar
    et al.
    Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics.
    Österberg, Jonas
    Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics.
    Silvestrov, Sergei
    Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics.
    Biteus, Jonas
    Scania CV, Sweden .
    Solving complex maintenance planning optimization problems using stochastic simulation and multi-criteria fuzzy decision making2014In: 10TH INTERNATIONAL CONFERENCE ON MATHEMATICAL PROBLEMS IN ENGINEERING, AEROSPACE AND SCIENCES: ICNPAA 2014 Conference date: 15–18 July 2014 Location: Narvik, Norway ISBN: 978-0-7354-1276-7 Editor: Seenith Sivasundaram Volume number: 1637 Published: 10 december 2014, American Institute of Physics (AIP), 2014, p. 766-775Conference paper (Refereed)
    Abstract [en]

    One of the most important factors in the operations of many cooperations today is to maximize profit and one important tool to that effect is the optimization of maintenance activities. Maintenance activities is at the largest level divided into two major areas, corrective maintenance (CM) and preventive maintenance (PM). When optimizing maintenance activities, by a maintenance plan or policy, we seek to find the best activities to perform at each point in time, be it PM or CM. We explore the use of stochastic simulation, genetic algorithms and other tools for solving complex maintenance planning optimization problems in terms of a suggested framework model based on discrete event simulation.

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