Demand management to cope with routes disruptions in location-inventory-routing problem for perishable products.

In today's competitive world, with the increase in the complexity of supply chains, supply chain vulnerability to disruptions has increased. In this research, a multi-period location-inventory-routing (LIR) problem of perishable products is investigated under the disruption of routes in some periods. To make a resilient supply chain, two types of pricing namely dynamic pricing and disruptive pricing are applied to manage demands along with location, inventory, and routing decisions. In this regard, an integrated LIR model is developed considering disruption in routes, price-sensitive demand, and a product with a certain life-time. In this model, the price of retailers is a descending function of the time and product lifetime. The proposed model is devised as a mixed-integer non-linear programming model that maximizes the total profit of the supply chain. Due to the NP-hard nature of the problem, the research has developed an efficient genetic algorithm to solve large-sized problems. Computational experiments conducted indicating that the projected GA has an average gap of less than 2.66% from the optimal solution within a reasonable time. The performance of the integrated model, the efficiency of the proposed resilient strategy, and the impact of shelf-life are investigated in a case study. Results revealed that the integrated model for dynamic pricing and LIR decisions enjoys 79.33% improvement in the total expected profit for the supply chain under disruption compared to static pricing. As expected, by increasing the product's shelf-life, the profit of the supply chain increases in all pricing policies. It should be noted that applying the dynamic pricing policy, compared to the product's lifetime, enjoys a greater impact on supply chain profit under disruption. Moreover, there is a necessity to choose an appropriate pricing policy for markets with a different value of price elasticity.