An Evolutionary Discrete Firefly Algorithm with Novel Operators for Solving the Vehicle Routing Problem with Time Windows

Abstract

An evolutionary discrete version of the Firefly Algorithm (EDFA) is presented in this chapter for solving the well-known Vehicle Routing Problem with Time Windows (VRPTW). The contribution of this work is not only the adaptation of the EDFA to the VRPTW, but also with some novel route optimization operators. These operators incorporate the process of minimizing the number of routes for a solution in the search process where node selective extractions and subsequent reinsertion are performed. The new operators analyze all routes of the current solution and thus increase the diversification capacity of the search process (in contrast with the traditional node and arc exchange based operators). With the aim of proving that the proposed EDFA and operators are effective, some different versions of the EDFA are compared. The present work includes the experimentation with all the 56 instances of the well-known VRPTW set. In order to obtain rigorous and fair conclusions, two different statistical tests have been conducted.

Mathematical Modeling and Discrete Firefly Algorithm to Optimize Scheduling Problem with Release Date, Sequence‐Dependent Setup Time, and Periodic Maintenance

“…The FA was primarily developed for continuous optimization [36], which attracted many researchers to adopt the classic FA to a discrete version to solve different discrete problems such as the scheduling problem [37,38] and vehicle routing [35,39]. The primary steps of our EDFA are presented as follows.…”

An Improved Cuckoo Search for a Patient Transportation Problem with Consideration of Reducing Transport Emissions

“…In the recent years, it has become an emerging trend in the field of meta-heuristic algorithms to develop bio-inspired algorithms and such algorithms have been widely applied to different scientific and engineering fields [24]. Furthermore, since Thangiah et al [25] first reported the application of bio-inspired algorithm to the VRP, a large number of proposals have appeared for solving numerous VRP variants [26] with good experimental results [27][28][29][30].…”

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“…Additionally, in [56] Osaba et al also shown that the FA is able to face complex routing problem, such as the asymmetric and clustered VRP with simultaneous pickup and deliveries, variable costs and forbidden paths. Finally, in [54], the same authors presented a evolutionary discrete FA with a novel operator to deal with VRP with time windows with successful results.…”