Use of GVRP as a Model of Two Specific Real World Problems and Its Bioinspired Solution

Abstract

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.

An Application of the DHI Methodology for a Comparison of SARS-CoV-2 Epidemic Hazards in Customer Delivery Services of Smart Cities

“…(1) -social distance of contact with another person for the mechanism of infection by droplets The factors presented in Table 1 are related to passenger and freight transport. For the assessment of only freight transport, as in cases of customer delivery services, the overall assessment is limited to factors such as social distance (1), touching a surface (2), loading time (3), isolation time (4), time between uses (6), operator exposure time (7), number of delivery stops (10), air circulation (11), type of loading (12), securing the cargo (13), document flow (14), and type of delivery point (15), which are 12 through 15 and written in italics in Table 1.…”

“…Smart city challenges also deal with generalized vehicle routing problem (GVRP). The paper [14] presents a method based on bio-inspired algorithms in order to find the optimum routing of product delivery.…”