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"A Fuzzy-Based Requirement Selection Method for Considering Value Depen" by Davoud Mougouei, Aditya Ghose et al.

Requirement selection is an essential component of software release planning, which finds, for a given budget, an optimal subset of the requirements with the highest value. However, due to the dependencies among software requirements, selecting or ignoring a requirement may impact the values of others. But such Value Dependencies are imprecise and hard to capture; they have been ignored by the existing requirement selection methods, increasing the risk of value loss in software projects. To address this, we have proposed a fuzzy-based optimization method with two main components: (i) a fuzzy-based technique for modeling value dependencies and capturing their imprecision, and (ii) an Integer Linear Programming (ILP) model that takes into account value dependencies in software requirement selection. The scalability and effectiveness of the method in mitigating value loss are demonstrated through simulations. ....

Value Dependencies , Integer Linear Programming , Requirement Selection , Alue Dependency ,

"A simulation-based solution approach for the robust capacitated vehicl" by Marcella Bernardo, Bo Du et al.

This article introduces a solution approach for the Stochastic Capacitated Vehicle Routing Problem (SCVRP) with uncertain demands, called Robust Simulation-Based (RoSi) approach. RoSi aims at designing route plans that can be more or less robust based on a decision-maker weight, i.e. solutions that resist demand changes with marginal additional (recourse) cost. For that, RoSi combines simulation with heuristics. It transforms a complex SCVRP into a set of deterministic ones, where well-known heuristics can be applied, computing a set of feasible solutions. These solutions are assessed by Monte Carlo simulation, and the one that deals better with demand fluctuation is selected as the final solution. The efficiency of RoSi is compared with those of three methods in the literature: Integer Linear Programming (ILP) model, Stochastic Programming with Recourse (SPR) model, and Robust Bi-Objective (RoBi) approach through numerical experiments. The results show that RoSi outperforms these meth ....

Monte Carlo , Stochastic Capacitated Vehicle Routing Problem , Robust Simulation Based , Integer Linear Programming , Stochastic Programming , Robust Bi Objective , Capacitated Vehicle Routing Problem , Ybrid Algorithms , Monte Carlo Simulation , Simulation Based Approach , Tochastic Demands ,

"Dependency-aware software requirements selection using fuzzy graphs an" by Davoud Mougouei and David M.W. Powers

Abstract
One of the critical activities in software development is Requirements Selection, which is to find an optimal subset of the software requirements (features) with the highest value for a given budget. The values of the requirements, however, may depend on one another. Such Value Dependencies have not been considered by the existing requirements selection methods, leading to user dissatisfaction and loss of value and reputation in software projects. To mitigate this, we propose Dependency-Aware Requirements Selection (DARS) as an expert system, which explicitly accounts for value dependencies in software projects. At the heart of DARS is an Integer Linear Programming (ILP) model that reduces the risk of value loss by considering value dependencies among the requirements. These value dependencies are identified from the preferences of the users for the requirements. The validly of DARS is verified by studying a real-world software project as well as carrying out simulati ....

Requirements Selection , Value Dependencies , Dependency Aware Requirements Selection , Integer Linear Programming , Integer Programming , தேவைகள் தேர்வு , மதிப்பு சார்புகள் , சார்பு விழிப்புணர்வு தேவைகள் தேர்வு , முழு நேரியல் ப்ரோக்ராமிஂக் ,