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We also provide computational results that show excellent solution times on small to medium sized problems.
The resulting system achieves the aim of providing real-time update of contours for small to medium sized problems on a PC.
Numerical results show that the designed Lagrangian relaxation method provides much better schedules and converges faster for small to medium sized problems, especially for larger sized problems.
For the small to medium sized problems that are the focus of the work, it cannot be assumed that the solution phase dominates, and so the evaluation of boundary integrals is considered as well as the equation solution.
We then model and solve the EV-to-trip scheduling problem offline and optimally using Mixed Integer Programming MIPP) techniques and show that the solution scales up to medium sized problems.
When some EVs do not have a large enough battery to execute some of the longest trips, the incremental-MIP generates solutions slightly better than the greedy, while the optimal algorithm is the best but scales up to medium sized problems only.
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A fuzzy multi-objective programming based approach is presented to solve the small and medium size problems to optimality.
We presented two methods to solve the problem and we concluded that their performance was acceptable for small and medium size problems, but not for large problems.
The results show that for small and medium size problems whether or not a computationally more demanding algorithm is employed to solve the level 1 or level 2 problem does not have any bearing on the makespan evaluated.
Using optimality conditions, we reformulate the non-linear bi-level model as a single-level mixed integer linear program, which is computationally tractable for medium size problems using a commercial solver.
By 'real-time' we mean that the optimization algorithm executes much faster than a typical or generic method with a human in the loop, in times measured in milliseconds or microseconds for small and medium size problems, and (a few) seconds for larger problems.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com