Abstract
This paper develops a new mathematical model to study a location-routing problem with simultaneous pickup and delivery under the risk of disruption. A remarkable number of previous studies have assumed that network components (e.g., routes, production factories, depots, etc.) are always available and can permanently serve the customers. This assumption is no longer valid when the network faces disruptions such as flood, earthquake, tsunami, terrorist attacks and workers strike. In case of any disruption in the network, tremendous cost is imposed on the stockholders. Incorporating disruption in the design phase of the network will alleviate the impact of these disasters and let the network resist disruption. In this study, a mixed integer programming (MIP) model is proposed that formulates a reliable capacitated location-routing problem with simultaneous pickup and delivery (RCLRP-SPD) services in supply chain distribution network. The objective function attempts to minimize the sum of location cost of depots, routing cost of vehicles and cost of unfulfilled demand of customers. Since the model is NP-Hard, three meta-heuristics are tailored for large-sized instances and the results show the outperformance of hybrid algorithms comparing to classic genetic algorithm. Finally, the obtained results are discussed and the paper is concluded.
Highlights
Chain management (SCM) consists of efficiently planning, implementing and controlling the supply chain operations
Besides to the proposed hybridizing the GA with VND (HGAVND) and HGALS algorithms, we employ classical genetic algorithms (GAs) to better show how these hybridizations improve the performance of the classical GA
This paper develops a new mixed-integer mathematical model for a reliable capacitated location-routing problem with simultaneous pickup and delivery, wherein the depots are exposed to the risk of disruption
Summary
Chain management (SCM) consists of efficiently planning, implementing and controlling the supply chain operations. In designing a distribution network, decisions vary from the number of echelons in the network to the optimal location(s) of the facilities These decisions are often classified into strategic, tactical, and operational decisions. Operational risks do not affect the functionality of supply chain’s elements and only affect operational factors that are supposed to be fundamentally uncertain They are typically inherent uncertainties in input parameters of a problem such as customer demand, purchasing prices for raw materials or required resources, production costs, transportation costs, lead times or transportation times. This paper aims at developing a RCLRP-SPD, wherein the impact of disruption of depots is investigated in both the location of depots and the routing of the vehicles through the customers.
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