Cat Swarm Optimization with Different Binarization Methods for Solving Set Covering Problems
نویسندگان
چکیده
In this paper, we present a Binary cat swarm optimization for solving the Set covering problem. The Set covering problem is a well-known NP-hard problem with many practical applications, including those involving scheduling, production planning and location problems. Binary cat swarm optimization is a recent swarm metaheuristic technique based on the behaviour of discrete cats. Domestic cats show the ability to hunt and are curious about moving objects. The cats have two modes of behavior: seeking mode and tracing mode. Moreover, eight different transfer functions and five discretization techniques are considered for solving the binary problem. We illustrate this approach with 65 instances of the problem and select the best transfer function and discretization technique to solve this problem.
منابع مشابه
Solving Data Clustering Problems using Chaos Embedded Cat Swarm Optimization
In this paper, a new method is proposed for solving the data clustering problem using Cat Swarm Optimization (CSO) algorithm based on chaotic behavior. The problem of data clustering is an important section in the field of the data mining, which has always been noted by researchers and experts in data mining for its numerous applications in solving real-world problems. The CSO algorithm is one ...
متن کاملSolving Data Clustering Problems using Chaos Embedded Cat Swarm Optimization
In this paper, a new method is proposed for solving the data clustering problem using Cat Swarm Optimization (CSO) algorithm based on chaotic behavior. The problem of data clustering is an important section in the field of the data mining, which has always been noted by researchers and experts in data mining for its numerous applications in solving real-world problems. The CSO algorithm is one ...
متن کاملSolving Fractional Programming Problems based on Swarm Intelligence
This paper presents a new approach to solve Fractional Programming Problems (FPPs) based on two different Swarm Intelligence (SI) algorithms. The two algorithms are: Particle Swarm Optimization, and Firefly Algorithm. The two algorithms are tested using several FPP benchmark examples and two selected industrial applications. The test aims to prove the capability of the SI algorithms to s...
متن کاملCat swarm optimization for solving the open shop scheduling problem
This paper aims to prove the efficiency of an adapted computationally intelligence-based behavior of cats called the cat swarm optimization algorithm, that solves the open shop scheduling problem, classified as NP-hard which its importance appears in several industrial and manufacturing applications. The cat swarm optimization algorithm was applied to solve some benchmark instances from the lit...
متن کاملSolving Biobjective Set Covering Problem Using Binary Cat Swarm Optimization Algorithm
The set cover problem is a classical question in combinatorics, computer science and complexity theory. It is one of Karp’s 21 NP-complete problems shown to be NP-complete in 1972. Several algorithms have been proposed to solve this problem, based on genetic algorithms (GA), Particle Swarm Optimizer (PSO) and in recent years algorithms based in behavior algorithms based groups or herds of anima...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2016