This paper proposes a heuristic approach for planning the activity of multiple carriers cooperating with the goal of eliminating empty truck trips while maximizing the cost saving resulting from their collaboration. The approach foresees three main phases: in the first step, the transportation demand is decomposed in two parts based on freight flows trade-off; in the second step, a linear optimization model, which takes into account compensation mechanisms among carriers, allows to combine two by two trips belonging to different carriers in order to decrease the number of empty movements. In this second phase, the importance of customers is explicitly taken into account by assigning to each trip a preference value. Finally, in the third step, a second optimization problem enables assigning, for each carrier, trucks to trips with the goal of minimizing their travel costs. The proposed heuristic approach has been tested on some instances and the results obtained are analyzed and discussed in the paper.
Planning truck carriers operations in a cooperative environment / Caballini, Claudia; Sacone, Simona; Saeednia, Mahnam. - STAMPA. - (2014), pp. 5121-5126. (Intervento presentato al convegno 19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014 tenutosi a Cape Town, SOUTH AFRICA nel Aug. 24-29, 2014) [10.3182/20140824-6-ZA-1003.02149].
Planning truck carriers operations in a cooperative environment
CABALLINI, CLAUDIA;
2014
Abstract
This paper proposes a heuristic approach for planning the activity of multiple carriers cooperating with the goal of eliminating empty truck trips while maximizing the cost saving resulting from their collaboration. The approach foresees three main phases: in the first step, the transportation demand is decomposed in two parts based on freight flows trade-off; in the second step, a linear optimization model, which takes into account compensation mechanisms among carriers, allows to combine two by two trips belonging to different carriers in order to decrease the number of empty movements. In this second phase, the importance of customers is explicitly taken into account by assigning to each trip a preference value. Finally, in the third step, a second optimization problem enables assigning, for each carrier, trucks to trips with the goal of minimizing their travel costs. The proposed heuristic approach has been tested on some instances and the results obtained are analyzed and discussed in the paper.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2834326