Capacitor allocation plays a vital role in the planning and operation of distribution networks. Optimal allocation of capacitor provides reactive power compensation, relieves feeder capacity, improves voltage profile, minimizes power losses, annual cost, and maximizes net savings. However, optimal capacitor allocation is a complex combinatorial optimization problem which consists of finding the bus location, number of capacitors to be installed and their respective sizes by satisfying all the distribution network constraints. The present article investigates the effective implementation of two novel metaheuristic algorithms for solving capacitor allocation optimization problems in the radial distribution network (RDN). The first algorithm is inspired by the water cycle process of nature in the real world where streams and rivers flow to the sea known as the water cycle algorithm (WCA). The second algorithm is inspired by salp swarming behavior in oceans for navigating and foraging is known as the salp swarm algorithm (SSA). To crisscross the feasibility, WCA and SSA are tested on standard 9, 33, 34, 69, and 85 — bus RDNs. Both the algorithms require less computational time for evaluating the objective function and only a few parameters need to be tuned. In addition, to show the superiority of the results obtained by WCA and SSA comparison has been made with various existing optimization techniques. The comparison confirms that both algorithms are more effective in minimizing power losses and operating costs and well suitable for solving capacitor allocation problems in RDNs.