Optimizing Bidders Selection of Multi-Round Procurement Problem in Software Project Management Using Parallel Max-Min Ant System Algorithm

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.

Software Project Management Approaches for Global Software Development： A Systematic Mapping Study

Global Software Development （GSD） is a well established field of software engineering with the benefits of a global environment. Software Project Management （SPM） plays a key role in the success of GSD. As a result, the need has arisen to study and evaluate the downsides of SPM for GSD, to thereby pave the way for the development of new methods, techniques, and tools with which to tackle them. This paper aims to identify and classify research on SPM approaches for GSD that are available in the literature, to identify their current weaknesses and strengths, and to analyze their applications in industry. We performed a Systematic Mapping Study （SMS） based on six classification criteria. Eighty-four papers were selected and analyzed. The results indicate that interest in SPM for GSD has been increasing since 2006. As a class of approaches, the most frequently reported methods （40%） are those used for coordination, planning, and monitoring, along with estimation techniques that can be used to better match a distributed project. SPM for GSD requires further investigation by researchers and practitioners, particularly with respect to cost and time estimations. These findings will help overcome the challenges that must to be considered in future SPM research for GSD, especially regarding collaboration and time-zone differences.

How to manage a task-oriented virtual assistant software project:an experience report

Task-oriented virtual assistants are software systems that provide users with a natural language interface to complete domain-specific tasks.With the recent technological advances in natural language processing and machine learning,an increasing number of task-oriented virtual assistants have been developed.However,due to the well-known complexity and difficulties of the natural language understanding problem,it is challenging to manage a task-oriented virtual assistant software project.Meanwhile,the management and experience related to the development of virtual assistants are hardly studied or shared in the research community or industry,to the best of our knowledge.To bridge this knowledge gap,in this paper,we share our experience and the lessons that we have learned at managing a task-oriented virtual assistant software project at Microsoft.We believe that our practices and the lessons learned can provide a useful reference for other researchers and practitioners who aim to develop a virtual assistant system.Finally,we have developed a requirement management tool,named SpecSpace,which can facilitate the management of virtual assistant projects.