Abstract
The drawback of several metaheuristic algorithms is the dropped local optimal trap in the solution to complicated problems. The diversity team is one of the promising ways to enhance the exploration of searching solutions in algorithm to avoid the local optimum trap. This paper proposes a diversity-team soccer league competition algorithm (DSLC) based on updating team member strategies for global optimization and its applied optimization of Wireless sensor network (WSN) deployment. The updating team consists of trading, drafting, and combining strategies. The trading strategy considers player transactions between groups after the ending season. The drafting strategy takes advantage of draft principles in real leagues to bring new players to the association. The combining strategy is a hybrid policy of trading and drafting one. Twenty-one benchmark functions of CEC2017 are used to test the performance of the proposed algorithm. The experimental results of the proposed algorithm compared with the other algorithms in the literature show that the proposed algorithm outperforms the competitors in terms of having an excellent ability to achieve global optimization. Moreover, the proposed DSLC algorithm is applied to solve the problem of WSN deployment and achieved excellent results.
Highlights
Optimization is one of the most common problems found in life, e.g., engineering design, business planning, or even military applications
The experimental results of the diversity-team soccer league competition algorithm (DSLC) algorithm are compared with the Soccer league competition (SLC), genetic algorithm (GA) [40], and firefly algorithm (FA) [41] algorithms for the coverage of node problem of ofdetermining the optimal spatial node coverage of implementation Wireless sensor network (WSN) is layout in The the deployment studied to model objective function mathematically
The parameters are set for the metaheuristic algorithms: the DSLC, SLC, FA, and GA methods are the same condition to solve the same problem of the deployment WSN for comparing fairly
Summary
Optimization is one of the most common problems found in life, e.g., engineering design, business planning, or even military applications. The best fitness player is selected in the league as the optimal solution for a given optimization problem Since it was proposed in 2014, in a short time, the SLC algorithm has been successfully applied to solve problems in several areas, e.g., the design of urban water supply networks [19,20], knapsack problems [21], and set covering problems [22]. Beside tested with the benchmark functions, we apply the proposed method to solve the practical problem of deployment in Wireless Sensor Network (WSN). The proposed method of enhanced diversity team to improve the metaheuristic SLC is a promising way for optimizing the design and deployment of WSN successfully.
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