Paper Info
Title
A binary monkey search algorithm variation for solving the set covering problem
Abstract
In complexity theory, there is a widely studied grouping of optimization problems that belongs to the non-deterministic polynomial-time hard set. One of them is the set covering problem, known as one of Karp's 21-complete problems, and it consists of finding a subset of decision variables for satisfying a set of constraints at the minimum feasible cost. However, due to the nature of the problem, this cannot be solved using traditional complete algorithms for hard instances. In this work, we present an improved binary version of the monkey search algorithm for solving the set covering problem. Originally, this approximate method was naturally inspired by the cognitive behavior of monkeys for climbing mountains.We propose a new climbing process with a better exploratory capability and a newcooperation procedure to reduce the number of unfeasible solutions. For testing this approach, we present a detailed computational results section, where we illustrate how this variation of the monkey search algorithm is capable of reaching various global optimums for a well-known instance set from the easley's OR-Library and how it outperforms many other heuristics and meta-heuristics addressed in the literature. Moreover, we add a complete statistical analysis to show the effectiveness of the proposed approach with respect to the original version.
Year
DOI
Venue
2020
10.1007/s11047-019-09752-8
NATURAL COMPUTING
Keywords
DocType
Volume
Monkey search algorithm,Set covering problem,Metaheuristics,Parameter setting,Optimization problem
Journal
19.0
Issue
ISSN
Citations 
SP4.0
1567-7818
0
PageRank 
References 
Authors
0.34
0
9
Name
Order
Citations
PageRank
Broderick Crawford144673.74
Ricardo Soto219447.59
Rodrigo Olivares3459.07
Gabriel Embry400.34
Diego Flores500.34
Wenceslao Palma6685.92
Carlos Castro725529.05
Fernando Paredes823027.21
José-Miguel Rubio900.34