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A genetic algorithm integrated with the initial solution procedure and parameter tuning for capacitated P-median problem

Öksüz, Mehmet Kürşat; Büyüközkan, Kadir; Bal, Alperen; Satoğlu, Şule Itır

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<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:creator>Öksüz, Mehmet Kürşat</dc:creator>
  <dc:creator>Büyüközkan, Kadir</dc:creator>
  <dc:creator>Bal, Alperen</dc:creator>
  <dc:creator>Satoğlu, Şule Itır</dc:creator>
  <dc:description>The capacitated p-median problem is a well-known location-allocation problem that is NP-hard. We proposed an advanced
Genetic Algorithm (GA) integrated with an Initial Solution Procedure for this problem to solve the medium and large-size
instances. A 33 Full Factorial Design was performed where three levels were selected for the probability of mutation,
population size, and the number of iterations. Parameter tuning was performed to reach better performance at each
instance. MANOVA and Post-Hoc tests were performed to identify significant parameter levels, considering both computational
time and optimality gap percentage. Real data of Lorena and Senne (2003) and the data set presented by
Stefanello et al. (2015) were used to test the proposed algorithm, and the results were compared with those of the other
heuristics existing in the literature. The proposed GA was able to reach the optimal solution for some of the instances in
contrast to other metaheuristics and the Mat-heuristic, and it reached a solution better than the best known for the largest
instance and found near-optimal solutions for the other cases. The results show that the proposed GA has the potential to
enhance the solutions for large-scale instances. Besides, it was also shown that the parameter tuning process might improve
the solution quality in terms of the objective function and the CPU time of the proposed GA, but the magnitude of
improvement may vary among different instances.</dc:description>
  <dc:source>Neural Computing and Applications 35(14467)</dc:source>
  <dc:subject>Capacitated p-median problem</dc:subject>
  <dc:subject>Facility location</dc:subject>
  <dc:subject>Genetic algorithm</dc:subject>
  <dc:subject>Initial solution algorithm</dc:subject>
  <dc:subject>Parameter tuning</dc:subject>
  <dc:title>A genetic algorithm integrated with the initial solution procedure and parameter tuning for capacitated P-median problem</dc:title>
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