A solution framework for the integrated problem of cargo assignment, fleet sizing, and delivery planning in offshore logistics

Fuzzy-logic Approach to Estimating the Fleet Efficiency of a Road Transport Company: A Case Study of Agricultural Products’ Deliveries in Kazakhstan

“…Based on the results of the membership functions' evaluation, the fleet of trucks required for the transportation of goods to the Atameken-Agro client (with an average delivery distance of 656 km and mean consignment weight of 15 tons) in the form of a fuzzy set according to (5) and the obtained values of the membership function as the following fuzzy set: Each vehicle model corresponds to the value of the membership function for the mean weight of the shipment and the average distance of delivery that characterize the considered transport company's client. Similarly, we represent the fleet of trucks for other customers and summarize the results in Table 1.…”

“…The choice of the type of freight transport is an important part of modeling the demand for freight traffic, and the problem of forming a rational structure of the vehicles fleet is typical not only for road transport, but is relevant for rail [2,3], water [1,[4][5][6] and industrial modes of transport [7][8][9]. That problem also occupies an important place in organizing mixed supply chains or delivery schemes with cross-docking terminals [1,6,[10][11][12][13].…”

A solution framework for the integrated periodic supply vessel planning and port scheduling in oil and gas supply logistics

“…In addition, [22] dealt with the problem of scheduling cargo supplies to maritime units with time windows at base and clients, with a solution found in a two-step approach: first a heuristic was used to obtain an initial feasible solution, which is them use initialize solver to obtain final optimal schedule. Related problems were discussed in [23][24][25][26][27][28][29][30][31][32]. [23] proposed a methodology to determine optimal fleet on the liner shipping problem, using a multi-trip vehicle routing model with time constraints.…”

“…A nonlinear model combined onshore and offshore location and routing decisions was presented on the work of [31]. Finally, [32] proposed a methodology integrating a simulation framework of PSV activities with an embedded optimization model to evaluate different fleet management policies and loading strategies on port.…”

“…Assignment and flow constraints were maintained in this model (constraints (3), ( 4), (6), and ( 7) with i ∈ C ∪ S). Constraint (12) turned into the new constraints (32), which define the relation between arrival time from a maritime unit to his successor, including the wait times when opening hours must be respected. Constraint (13) turned into the new constraint (33), as the first maritime unit became the auxiliary node that represents the port departure time.…”