Assessing the Reliability of a Multistate Logistics Network under the Transportation Cost Constraint

Abstract

Reliability and transportation cost are two important indicators to measure the performance of logistics network. As a combination of reliability and transportation cost, the performance index ( , ) of logistics network is defined as the probability that at least units of flow demand can be successfully transmitted from the source to the destination with the total transportation cost less than or equal to . In this paper, an algorithm is developed to calculate ( , ) in terms of ( , )-minimal paths (( , )-MPs for short). The proposed algorithm employs a decomposition technique to divide the search space of ( , )-MPs such that the search space of ( , )-MPs can be dramatically reduced, and thereby ( , )-MPs can be efficiently obtained. An example is provided to illustrate the proposed algorithm. Finally, computational experiments conducted on one benchmark network indicate that the proposed method has an advantage over the existing methods. Hindawi Publishing Corporation

A Review of Research on The Reliability Assessment of Fresh Product Distribution Networks Considering Product Perishability Constraint

“…Lin [31] proposed an evaluation mechanism for the reliability of multi-state stochastic logistics networks considering time windows, and calculated it using the minimal path method and the recursive disjoin and algorithm. Zeng et al [32] studied the reliability evaluation methods of multi-state logistics networks under cost constraints and introduced an innovative algorithm to reduce the search scope for minimal paths. Xu Xiuzhen et al [33][34] , combining network redundancy edges and transcendental number theory, respectively constructed logistics network reliability assessment models and algorithms under transportation cost and distance constraints.…”

Resource Allocation Optimization Model of Collaborative Logistics Network Based on Bilevel Programming

“…Collaborative logistics network resource allocation process involves three levels, which are suppliers, transit warehouse, and vendors, so the bilevel programming model can be used to explain the relationship between every two levels of nods. At the same time, the stochastic constrained programming can protect model against uncertain influence, and it has been applied to the system dynamics, structural dynamics, and financial and other fields [13][14][15]. Therefore, this article will set up the three-level nodes relationship among the suppliers, transit warehouses, and retailers and establish a bilevel programming model with chance constrained to control uncertainty factors, so as to make the whole logistics network system optimal under meeting the nodes' profit of both sides.…”