An Endosymbiotic Evolutionary Algorithm for the Hub Location-Routing Problem

Abstract

We consider a capacitated hub location-routing problem (HLRP) which combines the hub location problem and multihub vehicle routing decisions. The HLRP not only determines the locations of the capacitatedp-hubs within a set of potential hubs but also deals with the routes of the vehicles to meet the demands of customers. This problem is formulated as a 0-1 mixed integer programming model with the objective of the minimum total cost including routing cost, fixed hub cost, and fixed vehicle cost. As the HLRP has impractically demanding for the large sized problems, we develop a solution method based on the endosymbiotic evolutionary algorithm (EEA) which solves hub location and vehicle routing problem simultaneously. The performance of the proposed algorithm is examined through a comparative study. The experimental results show that the proposed EEA can be a viable solution method for the supply chain network planning.

Location‐routing problem: a classification of recent research

“…The LRPSPD appeared in 13.06% works, while three articles presented a case study of pickup-and-delivery LRP in postal delivery context (Winkenbach et al, 2016;Karimi andSetak, 2018a, 2018b). Meanwhile, 5.86% works deal with the case when customer nodes require either delivery or pickup services (e.g., Sun, 2015;Dukkanci and Kara, 2017;Mousavi and Vahdani, 2017). Numerous works have incorporated the presence of time window constraints in their models, either in the form of soft time window constraints (e.g., Rabbani et al, 2018a;Veysmoradi et al, 2018;Wang et al, 2018bWang et al, , 2018cHu et al, 2019) as found in 6.31% works, or hard time window constraints (e.g., Ceselli et al, 2014;Koç et al, 2016a;Basirati et al, 2019;Capelle et al, 2019;Koç et al, 2019) as indicated in 16.67% works.…”

A Bi-Level Programming Approach to the Location-Routing Problem with Cargo Splitting under Low-Carbon Policies

“…Zhang et al [23] adopted an improved particle swarm optimization algorithm to solve the dynamic multi-objective LRP in the emergency response process of major oil spill accidents at sea. Sun [24] solved the capacitated hub LRP at the same time based on an endosymbiotic evolutionary algorithm. In addition, some scholars used hybrid algorithms to solve LRPs, such as Yu et al [25], who designed a hybrid genetic algorithm to solve LRP with capacity constraints.…”

“…Among them, Equation ( 23) is the upper model's objective function, which means that the distribution center's construction and operation cost is minimized. Constraint (24) indicates that the total carbon emissions generated by the distribution center and distribution process must not exceed the prescribed emission cap.…”

Shared Mechanism-Based Self-Adaptive Hyperheuristic for Regional Low-Carbon Location-Routing Problem with Time Windows

“…Problem Domain Review. LRP deals with the combination of two types NP-hard decisions that often emerge in logistics: the location-allocation problem (LAP) and vehicle routing problem (VRP) (Ouhader and Kyal) [8] (Sun) [9]. Among the applications of LRP, LRP considering environmental effect such as carbon emission/fuel consumption, namely, LCLRP, has recently emerged as one of the most addressed, which also handles two NP-hard problems: LAP and pollution-routing problem (PRP) (Bektas and Laporte) [10] or green vehicle routing problem (GVRP) (Liu et al) [11].…”

“…Constraint (8) guarantees that the number of edges entering and leaving each node is the same. Constraints (9) and (10) demonstrate that each client is serviced only once by a single depot and vehicle. Constraints (11)-(13) forbid infeasible routings that do not return to the departure depot.…”