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A credibility-constrained programming for reliable forward–reverse logistics network design under uncertainty and facility disruptions

This paper offers a credibility-constrained programming model for reliable design of an integrated forward–reverse logistics network with hybrid facilities under uncertainty and random facility disruptions. To tackle with this problem, a novel mathematical model is first developed that integrates the network design decisions in both forward and reverse flows and utilises reliability concepts to deal with facility disruptions. Then, the developed model is enhanced based on the credibility-constrained programing to cope with the epistemic uncertainties embedded in the model parameters. Since the hybrid distribution-collection facilities play an important role in both forward and reverse flows, it is supposed that they might be randomly disrupted. Several effective reliability strategies are considered to hedge against random facility disruptions. First, locating two types of hybrid facilities, namely, reliable and unreliable, is taken into account in the concerned logistics network when disruptions strike. Second, unreliable hybrid facilities are allowed to be partially disrupted, and thus a percentage of their capacities may be lost. However, they can still serve their customers with their remaining capacities. To compensate the lost capacity at unreliable hybrid facilities, a sharing strategy is also considered, in which goods can be shipped from reliable hybrid facilities to unreliable ones. Finally, several numerical experiments along with a sensitivity analysis are conducted to illustrate the significance and applicability of the developed model as well as the effectiveness of the credibility-based solution approach.