1. Introduction
The sparrow search algorithm (SSA) is an effective optimization technique, which simulates the group wisdom foraging and anti-predation behaviors of sparrows. Searching is the process which is to look into or over carefully or thoroughly in an effort to find or discover something [1]. In sparrow search is the simple act of gathering food, either for immediate consumption or future storage. The sparrows are generally gregarious birds and have various species. They are distributed in most parts of the world and like to live in places where the human life [2]. In addition to their importance of sparrows have been significant to human society in myriad ways Moreover, they are and mainly feed on seeds of grains or weeds. It is well known that the sparrows are common resident birds. In the comparison with many other small birds, the sparrow is strongly intelligent and has a strong memory [3]. The effectiveness of the SSA is evaluated to the optimization problems belongs common in the engineering applications and the techniques involved in SSA is to be implemented to solve global optimization problems because of its simplicity, flexibility and high efficiency.
2. Inspiration of SSA
The main inspiration of the SSA is the searching behavior of sparrow for food [4]. The main food of sparrow includes grains or weeds. Sparrows are opportunistic, intelligent feeders and often use a variety of feeding techniques, adapting their methods to best suit the current conditions of their habitat and prey [5]. To feed successfully, sparrow use an technique called foraging techniques which is defined as acquisition of food by searching, hunting, or the gathering of food. The foraging technique in sparrow is when a bird does detect a predator, one or more individuals give a chirp and the entire group flies away [6].
SSA observed that house sparrows showed high fidelity to their roles as producer or scrounger, leading them to speculate that PS roles could be individually fixed. However, later experiments showed that role consistency and flexibility vary greatly from species to species and also depend on experimental conditions [7]. While foraging, animals often utilize group members to obtain food. One way to describe this behavior is with the producer-scrounger (PS) model, where scroungers use social interaction to obtain food discovered by producers. Scroungers preferentially joined birds of lower dominance rank and high search activity. Producers with these qualities had fewer eating events with full access to seeds, suggesting that scrounging exacts a fetch on producers [8].
3. Lifecycle of sparrow
Sparrows are generally short-lived, with an average lifespan of two to three years [9]. The female incubates the eggs for 12 days and young fledge at when they are between 9 and 11 days old within a week they follow their parents in search of food. The parents also continue to feed them, bringing them such things as fat grubs, often as big as the fledglings’ own heads [10]. At the age of three or four weeks the young birds are fully capable of looking after themselves.Fledge is the stage in a young bird’s life when the feathers and wing muscles are sufficiently developed for flight [11]. It also describes the act of a chick’s parents raising it to a fully grown state. A young bird that has recently fledged but is still dependent upon parental care and feeding is called a fledgling. Adult stage is ready for searching food.
3. Lifecycle of sparrow
Sparrows are generally short-lived, with an average lifespan of two to three years [9]. The female incubates the eggs for 12 days and young fledge at when they are between 9 and 11 days old within a week they follow their parents in search of food. The parents also continue to feed them, bringing them such things as fat grubs, often as big as the fledglings’ own heads [10]. At the age of three or four weeks the young birds are fully capable of looking after themselves.Fledge is the stage in a young bird’s life when the feathers and wing muscles are sufficiently developed for flight [11]. It also describes the act of a chick’s parents raising it to a fully grown state. A young bird that has recently fledged but is still dependent upon parental care and feeding is called a fledgling. Adult stage is ready for searching food.
4. Role of producers and scroungers
Sparrows foraging in groups can obtain food by searching or by social interaction with other group members [12]. This scenario has been examined with the producer-scrounger (PS) model, where producers actively search for food and scroungers profit from producers’ efforts through joining or stealing. Formulated the feeding trials to regulate if certain individuals prefer producer or scrounger roles within a foraging group if the roles are consistent over consecutive trials and if dominance rank or relatedness affects joining behavior [13]. By analyzing patterns of joining behavior, we were also able to explore how certain characteristics of a producer might affect a scrounger’s decision to join and if this had negative consequences for the producer.
5. Flowchart of SSA
6. Pseudo code of SSA
7. Numerical Implementation of SSA
Step1. Set a population size T ≥ n.
Consider three variables x, y and z. The problem is to find the best set of values for x, y and z so that their total value is equal to a value t.
x + y + z = t (1)
Where sum x+y+z from derviating from t,
i.e. |x + y + z — t| = (2)
Step 2. Generate a random grouping of the sparrow in the current population.
The position of sparrows can be represented in the following matrix:
Step 3. Compare the fitness value of the sparrow n listed in the grouping, and copy the best one into the next generation. Discard the strings compared.
If n is the number of sparrows and x & y shows the dimension of the variables to be optimized. Then, the fitness value of all sparrows can be expressed as;
The function f(x) is approximated by a searching line through points that are a finite distance apart, we can expand as;
f (x) is the fitness of the nth design, and D is the set of nondominated points in the current population; it is assumed that each objective function has been scaled by dividing it by an appropriate positive constant [14]. Thus, with each iteration one must first determine all of the nondominated points before evaluating the fitness of the designs [15]. Note that the nondominated points have negative fitness values. This fitness function automatically penalizes clustering of the nondominated points [16]. Thus, compared with other selection approaches, this one is relatively simple and effective.
Step 4. If the grouping is exhausted, generate another new best one.
Where t indicates the current iteration, j =1, 2… d. Xt i, j, is the optimal position occupied by the producer.
Denotes the current worst and best solution in the global optimal location.
Step 5. Repeat Steps 3 and 4 until no more selections are required for the next generation.
8. Advantages and disadvantages of SSA
9. Application of SSA
- Travelling salesman problem [17].
- Data collection [18].
- Robot path planning problem [19].
- Engineering design problem [20].
Reference
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[3]. Barnard C, Sibly R (1981) Producers and scroungers: A general model and its application to captive flocks of house sparrows. Animal Behavior 29:543-550. doi: 10.1016/s0003-3472(81)80117-0
[4]. Barta Z, Liker A, Mónus F (2004) The effects of predation risk on the use of social foraging tactics. Animal Behavior 67:301-308. doi: 10.1016/j.anbehav.2003.06.0124.
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[12].Pomeroy, H., &Hepner, F. (1992).Structure of turning in air borne rock dove (Columbalivia) flocks. The Auk, 109(2), 256–267.
[13]. Pulliam, H. R. (1973). On the advantages of flocking. Journal of Theoretical Biology, 38,419–422. Rashedi, E., Nezamabadi-Pour, H., & Saryazdi, S. (2009). GSA: A gravitational search algorithm. Information Sciences, 179(13), 2232–2248.
[14].Wolpert, D.H., &Macready, W.G.(1997).No free lunch theorems for optimization. IEEE Transactions on Evolutionary Computation, 1(1), 67–82.
[15].Johnson, C., Grant, J. W. A., & Giraldeau, L.-A. (2001). The effect of handling time on interference among house sparrows foraging at different seeddensities.Behaviour, 138,597–614.
[16]. Karaboga, D. (2005). An idea based on honey bee swarm for numerical optimization (Technical report-TR06). Erciyes University, Engineering Faculty, Computer Engineering Department (Vol.129 (2), pp.2865–2874).
[17].Karaboga, D., & Basturk, B. (2007). A powerful and efficient algorithm for numerical function optimization: Artificial bee colony (ABC) algorithm. Journal of Global Optimization, 39 (3), 459–471.
[18].Kennedy,J.,&Eberhart,R.(1995).Particle swarm optimization. In IEEE international conference on neural networks proceedings (pp.1942–1948)
[19].Yang, X. S. (2010a). Firefly algorithm, stochastic test functions and design optimization. International Journal of Bio-Inspired Computation,2(2),78–84.
[20].Lendvai, A. Z., Barta, Z., Liker, A., & Bokony, V. (2004). The effect of energy reserveson social foraging: Hungry sparrows
Good explanation.. But it would be better if the proper shapes used for flowchart..
One of the best algorithm presented in your blog….flowchart structure is innovative….
Thank you for your support…
good work