Empirical Analysis of Two Different Metaheuristics for Real-World Vehicle Routing Problems

Solving real-world vehicle routing problems with time windows using virus evolution strategy

“…Caric et al presented the empirical analysis of iterated local search and simulated annealing for real-world VRPTWs in the area of the city of Zageb, the capital of Croatia [21]. The calculation of travel time is based on the average velocity on a particular street or road segments.…”

“…Recently, many researchers have been done for realworld VRPTWs [16,17,21,22]. A Geographic Information System (GIS) and travel time information on a road network are required to solve the real-world problems, while the Euclidean distance is used in the Solomon's benchmark problems.…”

A Modelling and Optimization Framework for Real-World Vehicle Routing Problems

“…Based on the assignment of weights to the closing part of a time windows and distances to the serving places, the Coefficient Weighted Distance Time Heuristics (CWDTH) has been developed (Galić et al, 2006b;Carić et al, 2007). In each iteration the algorithm simultaneously searches for the customer with the soonest closing time of requested delivery and minimum distance from the current vehicle position.…”

Solving Practical Vehicle Routing Problem with Time Windows Using Metaheuristic Algorithms

“…Savings of exchange move are expressed as the following sum: Source: prepared by the author on the basis of [13] It is important to note that each improvement operator among all feasible moves selects the one that will produce maximal saving u.…”

“…In the next step local search procedure is applied in order to produce solution sm which represents local optimum [13]. Solution sm is automatically accepted as starting point for next iteration if objective function yields better value than for solution s. Otherwise, acceptance criterion for solution sm follows the probability function known as Metropolis condition [11]:…”