A constructive heuristic for police patrol routing problems

Esam Taha Yassen, Anas Arram, Masri Ayob, Mohd Zakree Ahmad Nazri

Research output: Contribution to journalArticle

Abstract

Police patrol routing problem (PPRP) attracts researchers’ attention especially on artifitial inteligence. The challenge here is that a limited number of patrols cover a wide range of area that includes several hotspots. In this study, a new model for PPRP is proposed simulating the Solomon’s benchmark for vehicle routing problem with time windows. This model can solve this problem by maximising the coverage of hotspots with frequencies of high priority locations while ensuring the feasibility of routes. Two constructive greedy heuristics are developed to generate the initial solution of the PPRP: highest priority greedy heuristic (HPGH) and nearest neighbour greedy heuristic (NNGH). Experimental results show that the simulated Solomon’s benchmark is suitable to represent PPRP. In addition, results illustrate that NNGH is more efficient to construct feasible solution than HPGH.

Original languageEnglish
Pages (from-to)87-96
Number of pages10
JournalPertanika Journal of Science and Technology
Volume25
Issue numberS6
Publication statusPublished - 1 Jun 2017

Fingerprint

police
Police
Law enforcement
routing
heuristics
Benchmarking
Vehicle routing
researchers
Research Personnel
Heuristics

Keywords

  • Greedy heuristic
  • Police patrol routing problem
  • Vehicle routing

ASJC Scopus subject areas

  • Computer Science(all)
  • Chemical Engineering(all)
  • Environmental Science(all)
  • Agricultural and Biological Sciences(all)

Cite this

A constructive heuristic for police patrol routing problems. / Yassen, Esam Taha; Arram, Anas; Ayob, Masri; Ahmad Nazri, Mohd Zakree.

In: Pertanika Journal of Science and Technology, Vol. 25, No. S6, 01.06.2017, p. 87-96.

Research output: Contribution to journalArticle

@article{c2a4071041314dca8b42411f165e3442,
title = "A constructive heuristic for police patrol routing problems",
abstract = "Police patrol routing problem (PPRP) attracts researchers’ attention especially on artifitial inteligence. The challenge here is that a limited number of patrols cover a wide range of area that includes several hotspots. In this study, a new model for PPRP is proposed simulating the Solomon’s benchmark for vehicle routing problem with time windows. This model can solve this problem by maximising the coverage of hotspots with frequencies of high priority locations while ensuring the feasibility of routes. Two constructive greedy heuristics are developed to generate the initial solution of the PPRP: highest priority greedy heuristic (HPGH) and nearest neighbour greedy heuristic (NNGH). Experimental results show that the simulated Solomon’s benchmark is suitable to represent PPRP. In addition, results illustrate that NNGH is more efficient to construct feasible solution than HPGH.",
keywords = "Greedy heuristic, Police patrol routing problem, Vehicle routing",
author = "Yassen, {Esam Taha} and Anas Arram and Masri Ayob and {Ahmad Nazri}, {Mohd Zakree}",
year = "2017",
month = "6",
day = "1",
language = "English",
volume = "25",
pages = "87--96",
journal = "Pertanika Journal of Science and Technology",
issn = "0128-7680",
publisher = "Universiti Putra Malaysia",
number = "S6",

}

TY - JOUR

T1 - A constructive heuristic for police patrol routing problems

AU - Yassen, Esam Taha

AU - Arram, Anas

AU - Ayob, Masri

AU - Ahmad Nazri, Mohd Zakree

PY - 2017/6/1

Y1 - 2017/6/1

N2 - Police patrol routing problem (PPRP) attracts researchers’ attention especially on artifitial inteligence. The challenge here is that a limited number of patrols cover a wide range of area that includes several hotspots. In this study, a new model for PPRP is proposed simulating the Solomon’s benchmark for vehicle routing problem with time windows. This model can solve this problem by maximising the coverage of hotspots with frequencies of high priority locations while ensuring the feasibility of routes. Two constructive greedy heuristics are developed to generate the initial solution of the PPRP: highest priority greedy heuristic (HPGH) and nearest neighbour greedy heuristic (NNGH). Experimental results show that the simulated Solomon’s benchmark is suitable to represent PPRP. In addition, results illustrate that NNGH is more efficient to construct feasible solution than HPGH.

AB - Police patrol routing problem (PPRP) attracts researchers’ attention especially on artifitial inteligence. The challenge here is that a limited number of patrols cover a wide range of area that includes several hotspots. In this study, a new model for PPRP is proposed simulating the Solomon’s benchmark for vehicle routing problem with time windows. This model can solve this problem by maximising the coverage of hotspots with frequencies of high priority locations while ensuring the feasibility of routes. Two constructive greedy heuristics are developed to generate the initial solution of the PPRP: highest priority greedy heuristic (HPGH) and nearest neighbour greedy heuristic (NNGH). Experimental results show that the simulated Solomon’s benchmark is suitable to represent PPRP. In addition, results illustrate that NNGH is more efficient to construct feasible solution than HPGH.

KW - Greedy heuristic

KW - Police patrol routing problem

KW - Vehicle routing

UR - http://www.scopus.com/inward/record.url?scp=85044227697&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85044227697&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:85044227697

VL - 25

SP - 87

EP - 96

JO - Pertanika Journal of Science and Technology

JF - Pertanika Journal of Science and Technology

SN - 0128-7680

IS - S6

ER -