| Full text | |
| Author(s): |
Chaves, A. A.
;
Resende, M. G. C.
;
Silva, R. M. A.
Total Authors: 3
|
| Document type: | Journal article |
| Source: | JOURNAL OF NONLINEAR AND VARIATIONAL ANALYSIS; v. 8, n. 6, p. 27-pg., 2024-01-01. |
| Abstract | |
This paper proposes a problem-independent GRASP metaheuristic by using the random-key tic for combinatorial optimization that repeatedly applies a semi-greedy construction procedure followed by a local search procedure. The best solution found over all iterations is returned as the solution of the GRASP. Continuous GRASP (C-GRASP) is an extension of GRASP for continuous optimization in the unit hypercube. A random-key optimizer (RKO) uses a vector of random keys to encode a solution to a combinatorial optimization problem. It uses a decoder to evaluate a solution encoded by the vector of random keys. A random-key GRASP is a C-GRASP where points in the unit hypercube are evaluated employing a decoder. We describe random key GRASP consisting of a problem-independent component and a problem-dependent decoder. As a proof of concept, the random-key GRASP is tested on five NPhard combinatorial optimization problems: traveling salesman problem, tree of hubs location problem, Steiner triple covering problem, node capacitated graph partitioning problem, and job sequencing and tool switching problem. (AU) | |
| FAPESP's process: | 22/05803-3 - Cutting, packing, lot-sizing, scheduling, routing and location problems and their integration in industrial and logistics settings |
| Grantee: | Reinaldo Morabito Neto |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 18/15417-8 - Development of a hybrid metaheuristic with adaptive control flow and parameters |
| Grantee: | Antônio Augusto Chaves |
| Support Opportunities: | Research Grants - Young Investigators Grants - Phase 2 |