Wireless Sensor Network Coverage Optimization: Comparison of Local Search-Based Heuristics

Table 1

Selected papers on MLCP optimization with Disjoint Set Cover based approaches.

No.	Reference	Year	Brief information about the approach and its optimization goal
1	S. Slijepcevic and M. Potkonjak [10]	2001	The most constrained–minimally constraining covering heuristic maximizes the cardinality of the set of covers
2	M. Cardei and D. Z. Du [12]	2005	The problem of set cover maximization converted into maximum-flow problem is modeled and solved by mixed integer programming (MIP), and then a heuristic computes the covers based on the solution returned by MIP
3	C.-C. Lai et al. [14]	2007	A genetic algorithm finds the maximum number of covers using the idea of critical sensors (the sensors covering the most sparsely covered POIs) to find an upper bound of the number of covers
4	X.-M. Hu et al. [15]	2010	The schedule transition hybrid genetic algorithm with the forward encoding scheme for the representation of chromosomes and problem-specific operators maximizes the number of covers and schedules them for makespan maximization
5	N. Ahn and S. Park [16]	2011	a binary integer programming formulation and heuristics compute the maximum number of covers
6	J.-M. Gil and Y.-H. Han [17]	2011	A genetic algorithm using a two-dimensional chromosome and problem-specific operators finds and schedules a given number of covers for makespan maximization in directional sensor networks
7	R. Cerulli et al. [18]	2012	A greedy heuristic and exact approach based on the column generation technique find the maximum number of covers
8	Y. Lin et al. [19]	2012	An ant colony optimization-based approach finds the maximum number of covers
9	M. E. Keskin et al. [20]	2014	The period iteration heuristic and the sequential assignment heuristic maximize four design issues: sensor locations, activity scheduling, data, and mobile sink routes integrated into an integer linear programming model
10	L. Wang et al. [21]	2017	Whale group algorithm optimizes the cover in terms of overall network performance: coverage, node utilization, and energy consumption
11	S. Balaji et al. [22]	2020	a cuckoo search algorithm finds the maximum number of covers