This paper presents a Game-theoretic optimization via Parallel Min-Max Ant System (PMMAS) algorithm is used in practice to determine the Nash equilibrium value to resolve the confusion in choosing appropriate bidders of multi-round procurement problem in software project management. To this end, we introduce an approach that proposes: (i) A Game-theoretic model of multiround procurement problem (ii) A Nash equilibrium strategy corresponds to multi-round strategy bid (iii) An application of PSO for the determination of global Nash equilibrium. The balance point in Nash Equilibrium can help to maintain a sustainable structure not only in terms of project management but also in terms of future cooperation. As an alternative of procuring entities subjectively, a methodology to support decision making has been studied using Nash equilibrium to create a balance point on benefit in procurement where buyers and suppliers need multiple rounds of bidding. Our goal focus on the balance point in Nash Equilibrium to optimizing bidder selection in multi-round procurement which is the most beneficial for both investors and selected tenderers. Our PMMAS algorithm is implemented based on MPI (message passing interface) to find the approximate optimal solution for the question of how to choose bidders and ensure a path for a win-win relationship of all participants in the procurement process. We also evaluate the speedup ratio and parallel efficiency between our algorithm and other proposed algorithms. As the experiment results, the high feasibility and effectiveness of the PMMAS algorithm are verified.
In this paper, game-theoretic optimization by particle swarm optimization (PSO) is used to determine the Nash equilibrium value, in order to resolve the confusion in choosing appropriate bidders in multi-round procurement. To this end, we introduce an approach that proposes (i) a game-theoretic model of the multi-round procurement problem; (ii) a Nash equilibrium strategy corresponding to the multi-round strategy bid; and (iii) an application of PSO for the determination of the global Nash equilibrium point. The balance point in Nash equilibrium can help to maintain a sustainable structure, not only in terms of project management but also in terms of future cooperation. As an alternative to procuring entities subjectively, a methodology using Nash equilibrium to support decision-making is developed to create a balance point that benefits procurement in which buyers and suppliers need multiple rounds of bidding. To solve complex optimization problems like this, PSO has been found to be one of the most effective meta-heuristic algorithms. These results propose a sustainable optimization procedure for the question of how to choose bidders and ensure a win-win relationship for all participants involved in the multi-round procurement process.
Software reliability modelling is the mathematical technique used to evaluate the reliability of a software system. The non-homogeneous Poisson process is a prominent approach in this field. More than half of the models in this group are based on S-shaped functions, primarily the 2-parameter S-shaped function. This paper proposes a new model based on the 3-parameter S-shaped function, which is an expanded form of the 2-parameter S-shaped function obtained by adding a growth rate controller. Real data from industrial software development projects are used to verify the usability of the proposed model. The proposed model is shown to perform better than the existing models, especially with respect to the predictive performance. Furthermore, the rate of convergence of the proposed model is acceptable, with a rate of 76.47%.
There has been observed explosive growth in the development of mobile applications (apps) for Android and iOS operating systems, which has led to the direct impact towards mobile app development. In order to design and propose quality-oriented apps, it is the primary responsibility of developers to devote time and sufficient efforts towards testing to make the apps bug-free and operational in the hands of end-users without any hiccup. Manual testing procedures take a prolonged amount of time in writing test cases, and in some cases, the full testing requirements are not met. Besides, the insufficient knowledge of tester also impacts the overall quality and bug-free apps. To overcome the obstacles of testing, we propose a new testing methodology cum tool called “AgileUATM” which works primarily towards white-box and black-box testing. To evaluate the validity of the proposed tool, we put the tool in a real-time operational environment concerning mobile test apps. By using this tool, all the acceptance criteria are determined via user stories. The testers/developers specify requirements with formal specifications based on programs properties, predicates, invariants, and constraints. The results show that the proposed tool generated effective and accurate test cases, test input. Meanwhile, expected output was also generated in a unified fashion from the user stories to meet acceptance criteria. The proposed solution also reduced the development time to identify test data as compared to manual Behavior-Driven Development (BDD) methodologies. This tool can support the developers to get a better idea about the required tests and able to translate the customer’s natural languages to computer languages as well. This paper fulfills an approach to suitably test mobile application development.
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