# Job scheduling to minimise squared completion times using mixed 0-1 quadratic program

I have come across an Optimization question as follows:

There are $n$ jobs that have to be processed on a machine. The machine can process only one job at a time. The time taken to process job $i$ on the machine is $t_i$. For a given sequence of jobs on the machine, the completion time of job $i$ is the time at which the machine finishes processing job $i$. The goal is to find the sequence of jobs which minimises the sum of the squared completion times.

I have attempted to solve it as follows but am not sure if it's correct. In particular I'm unsure about the constraints for the binary variables.

Variables: Let $x_{ij}=1$, for $i \in {1,...,n}$, $j \in 1,...,n$, $j \neq i$ if job $i$ is completed after job $j$, 0 otherwise.
Let $y_i$, $i \in {1,...,n}$ be the completion time for job $i$.

Min. $\sum_{i=1}^n y_i^2$

s.t. $y_i - \sum_{j \neq i} t_j x_{ij} \quad \forall i \in {1,...,n}$

$\quad\; x_{ij} + x_{jk} - 2x_{ik} \leq 1 \quad \forall i \neq j \neq k$

$\quad\; \sum_{i \neq j} x_{ij} = \sum_{m=1}^{n-1}m$

$\quad\; x_{ij} \in {0,1} \quad \forall i \neq j$

$\quad\; y_i \in \mathbb{R}^+$