An improved optimization method based on the intelligent water drops algorithm for the vehicle routing problem

Booyavi, Zahra; Teymourian, Ehsan; Komaki, G.M.; Sheikh, Shaya

doi:10.1109/cipls.2014.7007162

Cited by 13 publications

(8 citation statements)

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“…The intelligent water drop algorithm has been applied in many natural sciences and engineering sciences, showing strong advantages and potential. Since then, the IWD algorithm has been applied to many combinatorial optimization problems, including TSP [26], multiple knapsack [27], vehicle routing [28], and job shop scheduling [29], and the results obtained are very satisfactory.…”

Section: Intelligent Water Drop Algorithmsmentioning

confidence: 99%

Vehicle Routing and Scheduling Optimization of Ship Steel Distribution Center under Green Shipbuilding Mode

Guo

Qing-hua

et al. 2019

Sustainability

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Timeliness of steel distribution centers can effectively ensure the smooth progress of ship construction, but the carbon emissions of vehicles in the distribution process are also a major source of pollution. Therefore, when considering the common cost of vehicle distribution, taking the carbon emissions of vehicles into account, this paper establishes a Mixed Integer Linear Programming (MILP) model called green vehicle routing and scheduling problem with simultaneous pickups and deliveries and time windows (GVRSP-SPDTW). An intelligent water drop algorithm is designed and improved, and compared with the genetic algorithm and traditional intelligent water drop algorithm. The applicability of the improved intelligent water drop algorithm is proven. Finally, it is applied to a specific example to prove that the improved intelligent water drop algorithm can effectively reduce the cost of such problems, thereby reducing the carbon emissions of vehicles in the distribution process, achieving the goals of reducing environmental pollution and green shipbuilding.

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Section: Intelligent Water Drop Algorithmsmentioning

confidence: 99%

Vehicle Routing and Scheduling Optimization of Ship Steel Distribution Center under Green Shipbuilding Mode

Guo

Qing-hua

et al. 2019

Sustainability

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“…Also, a cuckoo optimization algorithm was proposed to solve large scale problems that have no optimum solution. As future direction of research, one can apply Intelligent water drops (e.g., Booyavi et al, 2014) or Harmony search (e.g., Komaki et al, 2014) and compare them to the proposed COA in this study.…”

Section: Resultsmentioning

confidence: 98%

Group technology-based model and cuckoo optimization algorithm for resource allocation in cloud computing

et al. 2015

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The control of operational costs is one of the main goals of resource management problem in cloud computing (CC). This paper presents a new mathematical model based on group technology (GT) to map the virtual machines (VMs) to workflows in order to control some costs (e.g. transfer costs, penalty costs and server cost) when the VMs are running. GT is a well-known manufacturing technique in industrial environments which can control some measures (e.g. part movements, resource utilization). In large size problems a cuckoo optimization algorithm (COA) is proposed. To test the effectiveness of our approaches, we first generate a set of problems randomly and then compare the model and COA with a well-known algorithm in literature called Round robin (RR). Analyzing the computational results proves that our approaches give better performance than RR.

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“…In this review, we have identified the algorithmic ideas proposed to improve IWD since its initial publication in 2007. A few articles seek to overcome drawbacks and limitation of the algorithm (Msallam and Hamdan, 2011;Alijla et al, 2014), while others propose modifications to enhance its exploration-exploitation capabilities (Duan et al, 2008(Duan et al, , 2009Niu et al, 2012;Booyavi et al, 2014;Teymourian et al, 2016a). Although the research on IWD is not particularly rich, we found that almost everything proposed to modify this algorithm consists of ideas that were first proposed in the context of ACO.…”

Section: Modifications Of Iwdmentioning

confidence: 95%

“…This is a relatively minor modification that, in the case of ACO, was already present in its very first formulation (Dorigo et al, 1991b). Later, Booyavi et al (2014) and Teymourian et al (2016b) have proposed the use of a parameter λ to weight the importance of soil with respect to heuristic information. Also this weighting mechanism is a part of most ACO algorithms and in particular was already present in the very first ones (Dorigo and Stützle, 2004).…”

Section: Modifications Of Iwdmentioning

confidence: 99%

The intelligent water drops algorithm: why it cannot be considered a novel algorithm

2019

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In this article, we rigorously analyze the intelligent water drops (IWD) algorithm, a metaphor-based approach for the approximate solution of discrete optimization problems proposed by Shah-Hosseini in 2007. We demonstrate that all main algorithmic components of IWD are simplifications or special cases of ant colony optimization (ACO) and therefore IWD is simply a particular instantiation of ACO. We show that the natural metaphor of "water drops flowing in rivers removing the soil from the riverbed", the source of inspiration of IWD, is unnecessary, misleading and based on unconvincing assumptions of rivers dynamics and soil erosion that lack of a real scientific rationale. We carry out a detailed review of modifications and extensions proposed to IWD since its first publication in 2007. We find that research on IWD is for the most part misguided and that the vast majority of the ideas explored in the literature on IWD have been studied many years before in the context of ACO. Finally, we discuss the use of natural metaphors as a source of inspiration for optimization algorithms, which has become an extremely popular trend in the last fifteen years, and propose some criteria to limit their usage to the cases in which the metaphor is indeed useful.

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An improved optimization method based on the intelligent water drops algorithm for the vehicle routing problem

Cited by 13 publications

References 50 publications

Vehicle Routing and Scheduling Optimization of Ship Steel Distribution Center under Green Shipbuilding Mode

Vehicle Routing and Scheduling Optimization of Ship Steel Distribution Center under Green Shipbuilding Mode

Group technology-based model and cuckoo optimization algorithm for resource allocation in cloud computing

The intelligent water drops algorithm: why it cannot be considered a novel algorithm

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