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

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.

Download Full-text

New Instances for Maximum Weight Independent Set From a Vehicle Routing Application

SN Operations Research Forum ◽

10.1007/s43069-021-00084-x ◽

2021 ◽

Vol 2 (4) ◽

Author(s):

Yuanyuan Dong ◽

Andrew V. Goldberg ◽

Alexander Noe ◽

Nikos Parotsidis ◽

Mauricio G. C. Resende ◽

...

Keyword(s):

Vehicle Routing ◽

Real World ◽

Vehicle Routing Problem ◽

Independent Set ◽

Maximum Weight ◽

Routing Problem ◽

Independent Set Problem ◽

Maximum Weight Independent Set ◽

Large Size

AbstractWe present a set of new instances of the maximum weight independent set problem. These instances are derived from a real-world vehicle routing problem and are challenging to solve in part because of their large size. We present instances with up to 881 thousand nodes and 383 million edges.

Download Full-text

Solving Practical Vehicle Routing Problem with Time Windows Using Metaheuristic Algorithms

PROMET - Traffic&Transportation ◽

10.7307/ptt.v24i4.443 ◽

1970 ◽

Vol 24 (4) ◽

pp. 343-351 ◽

Cited By ~ 4

Author(s):

Filip Taner ◽

Ante Galić ◽

Tonči Carić

Keyword(s):

Vehicle Routing ◽

Real World ◽

Vehicle Routing Problem ◽

Time Windows ◽

Iterated Local Search ◽

Metaheuristic Algorithms ◽

Benchmark Problems ◽

Routing Problem ◽

Constructive Heuristics ◽

Initial Feasible Solution

This paper addresses the Vehicle Routing Problem with Time Windows (VRPTW) and shows that implementing algorithms for solving various instances of VRPs can significantly reduce transportation costs that occur during the delivery process. Two metaheuristic algorithms were developed for solving VRPTW: Simulated Annealing and Iterated Local Search. Both algorithms generate initial feasible solution using constructive heuristics and use operators and various strategies for an iterative improvement. The algorithms were tested on Solomon’s benchmark problems and real world vehicle routing problems with time windows. In total, 44 real world problems were optimized in the case study using described algorithms. Obtained results showed that the same distribution task can be accomplished with savings up to 40% in the total travelled distance and that manually constructed routes are very ineffective.

Download Full-text