A bi-objective hierarchical hub location model with facility failure

Abstract

In the most past hub location problem (HLP) studies, failure probability is limited to a constant value; while in reality, it depends on various factors including natural disasters such as floods and earthquakes, commodity flow, institutional elements such as strikes, and etc. This paper looks into the problem of hub network design through a new model. The problem is to maximize the network reliability and to minimize the total routing cost simultaneously. In order to provide a more realistic model, the hub's failure probabilities were considered as a function of the hub's incoming traffic. Reserve hub elements are also taken into account in the model with the aim of increasing network reliability. To solve the model, a non-dominated sorting genetic algorithm (NSGA-II) is presented. The parameters of the algorithm are tuned using Taguchi method. The proposed solution is then carried out in a case study where the results confirm the acceptable performance of the model and also sensitivity analysis is performed in order to describe the effects of critical parameters into objective functions.

Scheduling of transportation fleet based on the customer’s priority in a hub location problem

“…Dukkanci et al [20] used a non-linear programming framework to simulate the green hub placement issue while taking into account the weight and speed of vehicles. A methodology to simultaneously increase network resilience and reduce overall routing costs was put up by Babashahi et al [21]. The model was then solved using a nondominated sorting genetic algorithm.…”

“…vehicles must return from the previous trip, and all depart immediately to the customer zone j . Constraint (21), along with Constraint (28) state, if the vehicle v has not traveled from the hub k to the customer zone j , the start time of this trip is necessarily zero. Constraint (22) refers to the base time for the transportation fleet; In reality, each vehicle begins its first journey at the beginning of time.…”

Toward sustainability in designing agricultural supply chain network: A case study on palm date

“…The selection mechanism is one of the different points when using NRGA or NSGA-II, as the NRGA and NSGA-II use the roulette wheel and binary tournament, respectively [61]. Figure 6 shows the pseudocode of these two algorithms.…”