Vehicles robust scheduling of hazardous materials based on hybrid particle swarm optimisation and genetic algorithm

Abstract

This paper takes the vehicles scheduling of hazardous materials as the research object. First, considered the four objectives of risk minimization, cost minimization, risk equilibrium value minimization, and duration minimization, the vehicles robust scheduling of hazardous materials in multiple distribution centers with risk balance is constructed. Then, uncertain models are transformed into peer-to-peer models through the idea of robust discrete optimization. By introducing the crossover and mutation operators of genetic algorithm into particle swarm algorithm, a hybrid particle swarm algorithm is constructed, and three-stage coding rules are adopted. Finally, case study is exemplified to prove the feasibility of the model and algorithm. The results show that the obtained scheduling scheme for the vehicles of hazardous materials minimizes the risk value and makes the risk distribution more balanced for the government regulatory department, and the vehicle can avoid certain road sections with relatively large risk values. For transportation enterprises, the vehicle scheduling scheme for transporting hazardous materials minimizes the cost and shortens the task duration at the same time. In the case of risk uncertainty, different robust control parameters are introduced to make the vehicles robust scheduling of hazardous materials have different degrees of stability.

Optimization approach to the aircraft weight and balance problem with the centre of gravity envelope constraints

“…Notable works on heuristic methods include those of Larsen and Mikkelsen [23], Brosh [24], Amiouny et al [25], Wodziak and Fadel [26], Mathur [27], and Heidelberg et al [28]. More recently, similar approaches have been reported by Dahmani and Krichen [29], Dahmani and Krichen [30], Tang et al [31], Tang et al [32] and Ma et al [33]. Some heuristic methods have demonstrated the ability to obtain relatively optimal results, but tended to require considerable time to calculate solutions.…”

“…[32] and Ma et al. [33]. Some heuristic methods have demonstrated the ability to obtain relatively optimal results, but tended to require considerable time to calculate solutions.…”

Uncertain Multi-Objective Hazardous Materials Transport Route Planning Considering Resilience and Low–Carbon

“…Many papers [5] and [12] don't consider the change of the quantity of hazardous materials in transit, but in reality the greater the quantity, the more serious consequences may occur. In this paper, the risk is in a state of dynamic change with the choice of route.…”

“…As for carbon emissions, the estimation method in literature [19] Constraints ( 8)- (10) refer to three transport cost, risk and carbon emission respectively. Constraint (11) and (12) indicate that when transporting the same kind of hazardous materials, one retail can only be served by one vehicle. Constraint (13) represents flow constraint.…”

“…Moghaddam et al [29] applied the method of game theory to find the optimal path with total distance and total risk as the target in the case of uncertain customer demand and service time. Ma et al [12] solved the multi-objective problem of vehicle scheduling through the idea of robust discrete optimization in the case of uncertain risks. And consider the government and enterprise two aspects of different options.. Ziaei et al [14] considered various uncertainties such as accident probability and carbon emission factors, and utilized robust counterpart optimization to solve the multi-objective location-routing planning of multi-modal transportation.…”