Decision-makers in synchromodal transport (ST) have different preferences toward objectives, such as cost, time, and emissions. To solve the conflicts among objectives obtain preferred solutions, a preference-based multi-objective optimization model is developed. In ST, containers need to be transferred across modes, therefore problem formulated pickup delivery with transshipment. The of decisi...

Industrial optimization applications must be robust: they must provide good solutions to problem instances of different size and numerical characteristics, and must continue to work well when side constraints are added. A good testbed for constructing such a robust solver is a set of network design problem instances recently made public by France Telecom. Together, these instances comprise the ...

We present a data mining approach for reducing the search space of local search algorithms in large-scale set partitioning problems (SPPs). We construct a k-nearest neighbor graph by extracting variable associations from the instance to be solved, in order to identify promising pairs of flipping variables in the large neighborhood search. We incorporate the search space reduction technique into...

Research on metaheuristics has focused (novel) algorithmic development and competitive testing, both of which have been frequently argued to yield little generalizable knowledge. The main goal this paper is promote meta-analysis — a systematic statistical examination that combines the results several independent studies as more suitable way obtain problem- implementation-independent insights me...