Abstract
This paper analyses a single manufacturer and multiple buyers supply chain where each buyer faces a price-sensitive demand. The manufacturer produces the item at a finite rate and ships to the buyers in multiple shipments of equal sized sub-batches. These shipments are made using third-party logistics support. The transportation cost is assumed to depend upon vehicle type and on the buyer to which shipment is made. The problem of determining right inventory policies to maximise the overall supply chain profit is formulated as a mixed-integer nonlinear programming (MINLP) model and a meta-heuristic based on particle swarm optimisation (PSO) is also proposed. The sensitivity analyses carried out shows the impact of the change in vehicle capacities, setup cost, unit cost, production rate and holding rate of the manufacturer on inventory policy and its related costs. The sensitivity analysis will provide a practical guide to the managers in reacting to a certain change in some parameter values, such as in the eventuality of increase in the setup cost for taking production of a larger lot size in one setup and supply the same to the buyers in more number of sub-batches without changing the sub-batch size.
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