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EURO Journal on Computational Optimization is a peer-reviewed journal published by Springer Nature, covering Vehicle Routing Optimization Methods, Advanced Optimization Algorithms Research, Risk and Portfolio Optimization.
| Publisher | Springer Nature |
|---|---|
| Reference style | Numbered (Springer Basic) Numbered — [1], [2] in the text 1. Smith A, Jones B, Lee C (2023) A representative article title. EURO Journal on Computational Optimization 12:45–58
Formats any DOI in EURO Journal on Computational Optimization style. No sign-up. |
| Publishes research in | Vehicle Routing Optimization Methods Advanced Optimization Algorithms Research Risk and Portfolio Optimization Facility Location and Emergency Management Optimization and Packing Problems |
| ISSN | 2192-4406 |
| Citation impact (2-yr) | 1.59 |
| h-index | 27 |
| i10-index | 84 |
| Total citations | 3,122 |
| Article processing charge | $1,400 |
| Open access | Yes |
| Top institutions publishing here | Centre National de la Recherche Scientifique |
| Journal website | www.sciencedirect.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
In this paper, we survey the literature on matheuristics proposed to solve vehicle routing problems. A matheuristic makes use of mathematical programming models in a heuristic framework. Matheuristics have been applied to several different routing problems and include a number of different approaches. We propose a classification in three classes of matheuristics: decomposition approaches, improvement…
Bilevel optimization is a field of mathematical programming in which some variables are constrained to be the solution of another optimization problem. As a consequence, bilevel optimization is able to model hierarchical decision processes. This is appealing for modeling real-world problems, but it also makes the resulting optimization models hard to solve in theory and…
We propose a forward–backward proximal-type algorithm with inertial/memory effects for minimizing the sum of a nonsmooth function with a smooth one in the nonconvex setting. Every sequence of iterates generated by the algorithm converges to a critical point of the objective function provided an appropriate regularization of the objective satisfies the Kurdyka-Łojasiewicz inequality, which is…
This paper provides the convex hull description of the single thermal Unit Commitment (UC) problem with the following basic operating constraints: (1) generation limits, (2) start-up and shut-down capabilities, and (3) minimum up and down times. The proposed constraints can be used as the core of any unit commitment formulation to strengthen the lower bound…
This study investigates the progress made in lp and milp solver performance during the last two decades by comparing the solver software from the beginning of the millennium with the codes available today. On average, we found out that for solving lp/milp, computer hardware got about 20 times faster, and the algorithms improved by a…
