MWWO: Modified water wave optimization

Soltanian, Amin; Derakhshan, Fatemeh; Soleimanpour-Moghadam, Mohadeseh

doi:10.1109/csiec.2018.8405412

Cited by 7 publications

(4 citation statements)

References 7 publications

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“…Furthermore, results were described as an average of thirty runs. The parameter setting of the proposed WWO algorithm was based on the setting reported in Soltanian et al (2018).…”

Section: Resultsmentioning

confidence: 99%

“…WWO is a metaheuristic algorithm based on the shallow water wave concept and has been adopted to solve a wide range of constrained and unconstrained optimization problems (Soltanian et al, 2018;Zheng, 2015). The solution space of WWO is similar to the seabed area where each solution represents a "wave" and each wave is represented through height and wavelength.…”

Section: Water Wave Optimizationmentioning

confidence: 99%

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Healthcare Data Analysis Using Water Wave Optimization-Based Diagnostic Model

Kumar

Kaur

2021

Journal of Information and Communication Technology

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This paper presents a new diagnostic model for various diseases. In the proposed diagnostic model, a water wave optimization (WWO) algorithm was implemented for improving the diagnosis accuracy. It was observed that the WWO algorithm suffered from the absence of global best information and premature convergence problems. Therefore in this work, some improvements were proposed to formulate the WWO algorithm as more promising and efficient. The global best information issue was addressed by using an improved solution search equation and the aim of this was to explore the global best optimal solution. Furthermore, a premature convergence problem was rectified by using a decay operator. These improvements were incorporated in the propagation and refraction phases of the WWO algorithm. The proposed algorithm was integrated into a diagnostic model for the analysis of healthcare data. The proposed algorithm aimed to improve the diagnosis accuracy of various diseases. The diverse disease datasets were considered for implementing the performance of the proposed diagnostic model based on accuracy and F-score performance indicators, while the existing techniques were regarded to compare the simulation results. The results confirmed that the WWO-based diagnostic model achieved a higher accuracy rate as compared to existing models/techniques with most disease/healthcare datasets. Therefore, it stated that the proposed diagnostic model is more promising and efficient for the diagnosis of different diseases.

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“…Furthermore, results were described as an average of thirty runs. The parameter setting of the proposed WWO algorithm was based on the setting reported in Soltanian et al (2018).…”

Section: Resultsmentioning

confidence: 99%

Section: Water Wave Optimizationmentioning

confidence: 99%

Healthcare Data Analysis Using Water Wave Optimization-Based Diagnostic Model

Kumar

Kaur

2021

Journal of Information and Communication Technology

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“…In the general case, a wave can have n dimensions, corresponding to n aspects of the problem under examination. At each iteration of the algorithm, three operations are carried out on the waves to modify them and try to improve the current best solution of the problem; the operations are named propagation, refraction and breaking [26] and recall the natural behavior of waves. The development of the algorithm can be resumed in the following five steps [21]:…”

Section: Background: the Water Wave Optimization Algorithmmentioning

confidence: 99%

“…For sure, we mean to carry out a set of experiments on known benchmark sets (e.g., see [8] or [26]) and compare their results; a further possible research activity could also address the comparison of the results and the effectiveness of the algorithm with other metaheuristics (e.g., genetic algorithms), whose original formulation would probably need to be adapted for the resolution of the VRP problem with time windows, in case appropriate adaptations do not exist.…”

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confidence: 99%

An Adapted Version of the Water Wave Optimization Algorithm for the Capacitated Vehicle Routing Problem with Time Windows with Application to a Real Case Using Probe Data

2020

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Customers’ habits, as far as shipping requests are concerned, have changed in the last decade, due to the fast spread of e-commerce and business to consumer (B2C) systems, thus generating more and more vehicles on the road, traffic congestion and, consequently, more pollution. Trying to partially solve this problem, the operational research field dedicates part of its research to possible ways to optimize transports in terms of costs, travel times, full loads etc., with the aim of reducing inefficiencies and impacts on profit, planet and people, i.e., the well-known triple bottom line approach to sustainability, also thanks to new technologies able to instantly provide probe data, which can detail information as far as the vehicle behavior. In line with this, an adapted version of the metaheuristic water wave optimization algorithm is here presented and applied to the context of the capacitated vehicle routing problem with time windows. This latter one is a particular case of the vehicle routing problem, whose aim is to define the best route in terms of travel time for visiting a set of customers, given the vehicles capacity and time constraints in which some customers need to be visited. The algorithm is then tested on a real case study of an express courier operating in the South of Italy. A nearest neighbor heuristic is applied, as well, to the same set of data, to test the effectiveness and accuracy of the algorithm. Results show a better performance of the proposed metaheuristic, which could improve the journeys by reducing the travel time by up to 23.64%.

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Exponential Adaptive Strategy in Spider Monkey Optimization Algorithm

Sharma

et al. 2020

Advances in Intelligent Systems and Computing

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MWWO: Modified water wave optimization

Cited by 7 publications

References 7 publications

Healthcare Data Analysis Using Water Wave Optimization-Based Diagnostic Model

Healthcare Data Analysis Using Water Wave Optimization-Based Diagnostic Model

An Adapted Version of the Water Wave Optimization Algorithm for the Capacitated Vehicle Routing Problem with Time Windows with Application to a Real Case Using Probe Data

Exponential Adaptive Strategy in Spider Monkey Optimization Algorithm

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