A multi-product vehicle routing scheduling model with time window constraints for cross docking system under uncertainty: A fuzzy possibilistic-stochastic programming

Mathematical modeling of supply chain operations has proven to be one of the most complex tasksin the eld of operations management and operations research. despite the abundance of severalmodeling proposals in the literature; for vast majority of them, no eective universal application isconceived. this issue renders the proposed mathematical models inapplicable due largely to the factthat real-life supply chain problems are set forth in restrained terms or represented less strikingly thanthey would bear out. this paper is triggered to bridge this gap by proposing a universal mixed integerlinear programming (milp) framework which to large extent simulates many realistic considerationsin vehicle routing scheduling problems in cross-docking systems which might have separately beenattempted by other researchers. the developed model is pioneer in excogitating the vehicle routingscheduling problem with the following assumptions: a) multiple products are transported betweenpick-up and delivery nodes, b) delivery time-intervals are imposed on each delivery node, c) multipletypes of vehicles operate in the system, d) capacity constraints exists for each vehicle type, andnally e) vehicles arrives simultaneously at cross-docking location. moreover, to solve the model ahybrid solution methodology is presented by combining fuzzy possibilistic programming and stochasticprogramming. finally, in order to demonstrate the accuracy and eciency of the proposed model, anextensive sensitivity analysis is performed to scrutinize its parameters' demeanors.