The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Solving Facility Location Problems with a Tol for Rapid Development of Multi-Objective Evolutionary Algorithms (MOEAs)
Abstract
The low price of coffee in the international markets has forced the Federación Nacional de Cafeteros de Colombia (FNCC) to look for cost-cutting opportunities. An alternative that has been considered is the reduction of the operating infrastructure by closing some of the FNCC-owned depots. This new proposal of the coffee supplier network is supported by (uncapacitated and capacitated) facility location models that minimize operating costs while maximizing service level (coverage). These bi-objective optimization models are solved by means of NSGA II, a multi-objective evolutionary algorithm (MOEA). From a computational perspective, this chapter presents the multi-objective Java Genetic Algorithm (MO-JGA) framework, a new tool for the rapid development of MOEAs built on top of the Java Genetic Algorithm (JGA). We illustrate MO-JGA by implementing NSGA II-based solutions for the bi-objective location models.
Related Content
|
P. Chitra, A. Saleem Raja, V. Sivakumar.
© 2024.
24 pages.
|
|
K. Ezhilarasan, K. Somasundaram, T. Kalaiselvi, Praveenkumar Somasundaram, S. Karthigai Selvi, A. Jeevarekha.
© 2024.
36 pages.
|
|
Kande Archana, V. Kamakshi Prasad, M. Ashok.
© 2024.
17 pages.
|
|
Ritesh Kumar Jain, Kamal Kant Hiran.
© 2024.
23 pages.
|
|
U. Vignesh, R. Elakya.
© 2024.
13 pages.
|
|
S. Karthigai Selvi, R. Siva Shankar, K. Ezhilarasan.
© 2024.
16 pages.
|
|
Vemasani Varshini, Maheswari Raja, Sharath Kumar Jagannathan.
© 2024.
20 pages.
|
|
|