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We propose hereafter a method to heuristically solve the TDOP in two steps.
The rest of the paper is organized as follows: Section 2 provides the necessary terminology and makes a detailed description of constraints and objective function of the TDOP; a toy example is also furnished to help understand the problem.
This section is aimed to describe the TDOP, borrowing some terminology from .
The objective of the TDOP is to minimize the sum of eight components:
This section presents the algorithm developed by us to tackle the TDOP. It consists of two main steps.
Composed by substeps (1.1)-(1.3), this step is aimed to produce from scratch a feasible solution of the TDOP, namely, where constraints (6)-(11) are satisfied.
Let [PHI](J) denote the set of feasible solutions of an instance J of the TDOP. The neighborhood of a solution S [member of] [PHI](J) is
Our simulated annealing approach, as described in Section 4 to deal with the TDOP, was implemented on a computer with Xeon E5-2643 v2 3.5 GHz processor (we run in a single processor), 64 GB RAM, and g++ compiler.
y TDOP = [raiz cuadrada de [V.sub.T]/[[sigma].sub.[??]]]
Por el mismo razonamiento se pueden definir PDOP, TDOP, HDOP y VDOP, y por supuesto el NDOP y el EDOP (USAF, 1996) como
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- TDP II