“…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.…”
Section: Solutions For Real-world Problemsmentioning
confidence: 99%
“…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.…”
This paper proposes a new solution to the vehicle routing problem with time windows using an evolution strategy adopting viral infection. The problem belongs to the NP-hard class and is very difficult to solve within practical time limits using systematic optimization techniques. In conventional evolution strategies, a schema with a high degree-of-fitness produced in the process of evolution may not be inherited when the fitness of the individual containing the schema is low. The proposed method preserves the schema as a virus and uses it by the infection operation in successive generations. Experimental results using extended Solomon's benchmark problems with 1000 customers proved that the proposed method is superior to conventional methods in both its rates of searches and the probability of obtaining solutions. Further experiments using the map of the central part of Tokyo with 20000 intersections and real traffic data also gave that the rate of search of the proposed method is higher than that of the conventional method.
“…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.…”
Section: Solutions For Real-world Problemsmentioning
confidence: 99%
“…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.…”
This paper proposes a new solution to the vehicle routing problem with time windows using an evolution strategy adopting viral infection. The problem belongs to the NP-hard class and is very difficult to solve within practical time limits using systematic optimization techniques. In conventional evolution strategies, a schema with a high degree-of-fitness produced in the process of evolution may not be inherited when the fitness of the individual containing the schema is low. The proposed method preserves the schema as a virus and uses it by the infection operation in successive generations. Experimental results using extended Solomon's benchmark problems with 1000 customers proved that the proposed method is superior to conventional methods in both its rates of searches and the probability of obtaining solutions. Further experiments using the map of the central part of Tokyo with 20000 intersections and real traffic data also gave that the rate of search of the proposed method is higher than that of the conventional method.
“…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.…”
Section: Coefficient Weighted Distance Time Heuristics For Cvrptwmentioning
“…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.…”
Section: Figure 1 -Vrp Variants and Their Interconnectionsmentioning
confidence: 99%
“…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]:…”
Section: In Each Iteration Of the Main Loop Function Escape(s)mentioning
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