A robust optimization model for green regional logistics network design with uncertainty in future logistics demand

Abstract

This article proposes a new model to address the design problem of a sustainable regional logistics network with uncertainty in future logistics demand. In the proposed model, the future logistics demand is assumed to be a random variable with a given probability distribution. A set of chance constraints with regard to logistics service capacity and environmental impacts is incorporated to consider the sustainability of logistics network design. The proposed model is formulated as a two-stage robust optimization problem. The first-stage problem before the realization of future logistics demand aims to minimize a risk-averse objective by determining the optimal location and size of logistics parks with CO 2 emission taxes consideration. The second stage after the uncertain logistics demand has been determined is a scenario-based stochastic logistics service route choices equilibrium problem. A heuristic solution algorithm, which is a combination of penalty function method, genetic algorithm, and Gauss-Seidel decomposition approach, is developed to solve the proposed model. An illustrative example is given to show the application of the proposed model and solution algorithm. The findings show that total social welfare of the logistics system depends very much on the level of uncertainty in future logistics demand, capital budget for logistics parks, and confidence levels of the chance constraints.

Multimodal Green Logistics Network Design of Urban Agglomeration with Stochastic Demand

“…To route the flow of goods, multimodal transportation is a hybrid of transportation that involves two classic transportation services: the single mode of transport and combined transport [9]. Compared with the single transportation mode, the multimodal transportation can make full use of existing logistics networks of infrastructure and the advantage of various modes of transport, integrating transport capacity resources, meeting the transport demand, and achieving the target (e.g., time, cost, and profit) [10,11]. In the multimodal transportation, there is no effective connection between each mode of transportation, and the design of the multimodal transportation plan needs to be further improved and optimized [12].…”

“…For HGVs or LGVs, the Bureau of Public Roads-type (BPR) function can be adopted to estimate transport service time. For railways or waterways, we consider service time function as a function of link free-flow transport service time and departure interval time [11,35]. Similarly, for each virtual transfer arc, we use the following service time function:…”

Structure and toughness optimization of multi-layer weighted regional logistics network: taking the central region of China as an example

“…The concept of toughness was first introduced into the field of ecology in the 1970s [22] , and its application field has been continuously expanded since then. The toughness of regional logistics networks is mainly affected by the uncertainty level of future logistics demand and the operating costs of logistics nodes [23] , network toughness can be optimized by changing network agility, visibility, flexibility, collaboration and information sharing [24] . Zhang et al [25] proposed a method to measure the overall toughness of the network with node and edge indicators in the network, Ahmadian et al [26] proposed a quantitative analysis method to evaluate and improve network toughness, Gholizadeh et al [27] optimized the toughness of reverse logistics networks, Guo et al [28] improved the toughness of regional logistics distribution network based on cooperative coverage model.…”

Research on the Supernetwork Equalization Model of Multilayer Attributive Regional Logistics Integration

“…In this eld, there are three main directions: (1) Research on the construction of regional logistics network and its in uencing factors. For example, based on the perspective of optimal cost and value risk, domestic and foreign scholars put forward the design method of spoke structure network, as well as the delivery routes and scheduling of hub nodes [1][2][3][4]; or take a certain area as an actual case to study the positioning of logistics center in logistics transportation network [5][6][7]; or study the impact of system and policy on the construction of logistics network in coastal cities under similar conditions of natural environment and other characteristics [8][9][10]. (2) Research on the construction and optimization of regional logistics network.…”