A novel fuzzy bi-objective vehicle routing and scheduling problem with time window constraint for a distribution system: A case study

Abstract

In the process of hazardous material transportation, the risk is a significant factor that should be considered due to the potential severe consequence of an incident. Regardless of risks, time is a paramount concern that should be considered in hazardous material transportation. In this way, this paper introduces a bi-objective model for a vehicle routing and scheduling problem of hazardous material distribution problems under the fuzzy condition to minimize both total distribution time and risks. In the proposed model, the fuzzy inference system and fuzzy failure mode and effects analysis are applied to identify and calculate the high-level risks instead of the previous simple methods for the first time. Moreover, Jimenez method and fuzzy goal programming are respectively utilized to convert the fuzzy bi-objective model into the same crisp and single-objective one. Besides, to cope with the NP-hardness of the largesized problems, two meta-heuristic algorithms namely invasive weeds optimization and genetic algorithm is used, and several sensitivity analyses are performed to prove the efficiency of the proposed approach. The performance of the proposed algorithms is also assessed through a comparative study. Finally, the proposed model is implemented to a real case study to prove the validity of the model.

Route Optimization for Hazardous Chemicals Transportation under Time-Varying Conditions

“…Chai [16] proposed a new driving risk during hazardous chemicals transportation taking into account the risk evaluation model, and constructed a biobjective optimization model for minimizing the transportation risk and transportation cost, which was solved by using a modified nondominated sequential genetic algorithm. Esmaeilidoukia et al [17] proposed a fuzzy planning model for minimizing the time and risk, which was transformed into a deterministic model and then solved using an invasive weed algorithm.…”

“…Equation ( 15) provides the vehicle flow balance constraint for each node in the transportation network. Equation (17) indicates that the loading of the vehicle must meet the demand of the customer node to be served. Equation (18) indicates that the loading of each vehicle must not exceed the maximum loading of the transport vehicle.…”

“…As can be seen from the experimental results in Table 5, vehicles also have different objective function values when transporting hazardous chemicals along the same transportation routes at different departure times. Taking the routes r 1 1 and r 2 2 as examples, at the different departure times of 4:20 and 7:20, the transportation routes are both [1,3,4,11,14,15,10,17,10,11,4,3,1] and [1,3,4,11,10,16,18,16,8,6,2,1], but in terms of transportation cost, the transportation cost of r 1 1 is CNY 2646.93 higher than r 2 2 and the transportation cost of r 2 2 is CNY 2592.35. In terms of transportation risk, the transportation risk of r 1 1 is 20.47, which is higher than the transportation risk of r 2 2 .…”

Multi-depot home health care routing and scheduling problem with multimodal transportation: Mathematical model and solution methods

“…One of the meta-heuristics that can be used to solve combinatorial optimization problem such as HHCRSP is IWO algorithm that is introduced by Mehrabian and Lucas [25]. This method is a numerical stochastic optimization algorithm inspired by the fact of colonization of invasive weeds in nature based on weed biology and ecology [31]. IWO is an efficient and effective optimization tool by gradual evolution and inspired by the unique natural characteristics of weeds in seed production and cultivation.…”