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Tacit knowledge generates ambiguous,inappropriate and incomplete requirements, so it is extremelyimportant do a good job on gathering meaningful requirementsin order to obtain tailored high quality software. In this paper, arequirements engineering process model is presented, whichhas the aim of minimize the percentage of ambiguous,incomplete and not appropriate requirements and thus impacton software-solution quality, especially in domains where tacitknowledge has great relevance

The aim of this chapter is about the inclusion of real world scenarios, viewed as a Generalized Vehicle Routing Problem (GVRP) model problem, and treated by bio inspired algorithms in order to find optimum routing of product delivery. GVRP is the generalization of the classical Vehicle Routing Problem (VRP) that is well known NP-hard as generalized combinatorial optimization problem with a number of real world applications and a variety of different versions. Due to its complexity, large instances of VRP are hard to solve using exact methods. Thus a solution by a soft computing technique is desired. From a methodological standpoint, the chapter includes four bio inspired algorithms, ant colony optimization and firefly. From an application standpoint, several factors of the generalized vehicle routing are considered from a real world scenario.