Hybrid heuristics for minimum cardinality set covering problems

Vasko, Francis J.; Wilson, George R.

doi:10.1002/nav.3800330207

Cited by 32 publications

(5 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…LSCP is mainly to solve the location problem of emergency service facilities, which requires establishing as few service facilities as possible to cover all demand points [18] . And it has been widely used in the field of public facilities (hospitals) and emergency service facilities (fire centers) [19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35] . Using the LSCP to optimize the layout of monitoring network for mine water inrush can achieve two purposes: on the one hand, under the premise of meeting the timeliness requirements of monitoring water inrush, efforts should be made to minimize the cost, so as to effectively reduce the cost and avoid waste caused by unreasonable planning; On the other hand, ensure that the monitoring timeliness is optimized when the cost is fixed.…”

Section: Introductionmentioning

confidence: 99%

WITHDRAWN: Study on multi-constraint and multi-objective optimization layout method of monitoring network for mine water inrush

Qiang

Zhao

et al. 2022

Preprint

View full text Add to dashboard Cite

Disastrous water inrush often causes heavy property losses and even casualties, while the current theory and technology of mine water prevention and control can not accurately predict the time and place of disastrous water inrush in mine, so monitoring disastrous water inrush has become an urgent problem to be solved. Through the networked deployment of water level sensors in the roadway, this paper proposes a monitoring network for catastrophic water inrush in coal mine, and studies a multi-constraint and multi-objective optimal deployment method for the monitoring network. By setting three practical constraints of mining area, risk level of water inrush and installation at specified location, and constructing two objective functions of minimum total cost and minimum average monitoring time, a mathematical model is established, and then NSGA - Ⅱ multi-objective genetic algorithm is designed to solve the model. As results, the method can optimize the monitoring network for mine water inrush from two dimensions of time and space. The proposed method is then verified in the Beiyangzhuang coal mine in the North China. The results show that the average time of the catastrophic water inrush monitored can be controlled within 916 seconds by using only 28 water level sensors, and the higher the risk level of water inrush, the shorter the monitoring response time. Due to the constraints of installation at specified location, the monitoring network can also take into account monitoring the daily water inflow in the Beiyangzhuang coal mine.

show abstract

Section: Introductionmentioning

confidence: 99%

WITHDRAWN: Study on multi-constraint and multi-objective optimization layout method of monitoring network for mine water inrush

Qiang

Zhao

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The subproblem becomes the uncapacitated plant location model which we can solve using, (Vasko and Wilson [1986] • Selecting a "'robust'" set of blooms: one that minimizes manufacturing effort for the prefened tube-to-bloom assignments, but also provides an alternate bloom when the prefeired bloom is in short supply, del Callar [1992] has proposed and tested genetic algorithms for this model.…”

Section: -mentioning

confidence: 99%

Process Planning for Aluminum Tubes: An Engineering-Operations Perspective

Balakrishnan

Brown

1996

Operations Research

View full text Add to dashboard Cite

“…Additionally, Chaudhry [3] proposed and tested two additional heuristics for the CCP. Finally, Lotfi and Moon [10,11] improved upon the simple heuristics by incorporating facility exchange procedures into their techniques, which was an extension of the parallel efforts by Vasco and Wilson [18] on the set-covering problem.…”

Section: Introductionmentioning

confidence: 98%

Algorithms for solving the conditional covering problem on paths

Lunday

Smith

Goldberg

2005

Naval Research Logistics

View full text Add to dashboard Cite

Consider the conditional covering problem on an undirected graph, where each node represents a site that must be covered by a facility, and facilities may only be established at these nodes. Each facility can cover all sites that lie within some common covering radius, except the site at which it is located. Although this problem is difficult to solve on general graphs, there exist special structures on which the problem is easily solvable. In this paper, we consider the special case in which the graph is a simple path. For the case in which facility location costs do not vary based on the site, we derive characteristics of the problem that lead to a linear-time shortest path algorithm for solving the problem. When the facility location costs vary according to the site, we provide a more complex, but still polynomial-time, dynamic programming algorithm to find the optimal solution.

show abstract

Hybrid heuristics for minimum cardinality set covering problems

Cited by 32 publications

References 12 publications

WITHDRAWN: Study on multi-constraint and multi-objective optimization layout method of monitoring network for mine water inrush

WITHDRAWN: Study on multi-constraint and multi-objective optimization layout method of monitoring network for mine water inrush

Process Planning for Aluminum Tubes: An Engineering-Operations Perspective

Algorithms for solving the conditional covering problem on paths

Contact Info

Product

Resources

About