A chance constrained programming approach for HazMat capacitated vehicle routing problem in Type-2 fuzzy environment

Men, Jinkun; Jiang, Peng; Xu, Hao

doi:10.1016/j.jclepro.2019.117754

Cited by 44 publications

(14 citation statements)

References 27 publications

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“…In order to evaluate the solution more comprehensively, two concepts are introduced, tightness and unit cost. Tightness [54] is estimated by calculating the amount of waste carried per unit vehicle capacity, as shown in Equation (28). Unit cost is about the collection cost of per unit waste and is stated in Equation 29:…”

Section: Experimental Results Of Wfls and Credibility Levelsmentioning

confidence: 99%

“…Total collected waste NO.o f vehicles × Capacity o f vehicles (28) Unit Cost = Total cost Total collected waste…”

Section: Experimental Results Of Wfls and Credibility Levelsmentioning

confidence: 99%

“…Xu et al [27] constructed a model combining a genetic algorithm and fuzzy chance-constrained programming to support SWM under uncertainty conditions, and the applicability of the proposed model was demonstrated by a real reginal waste management issue. Men et al [28] considered a HazMat equipped vehicle routing problem (H-CVRP) in a type-2 fuzzy environment. Because of the stochastic variable of population density, the objective function involved trapezoidal interval type-1 variables, and was transformed into two equivalent constrains by chance-constrained programming.…”

Section: Research About Chance-constrained Programmingmentioning

confidence: 99%

“…The VRP problem is a NP-hard problem. Therefore, it is natural to use a heuristic to solve the problem [32], such as the adaptive Harmony Search Algorithm (HSA) [33], adaptive Large Neighborhood Search (LNS) algorithm [34], Iterated Greedy Algorithm (IGA) [35], Genetic Algorithm (GA) [3] and Particle Swarm Optimization (PSO) algorithm [36], Simulated Annealing Algorithm (SAA) [28,37,38], Multiple Neighborhood Search (MNS) algorithm [24], etc.…”

Section: Research About Some Algorithms For Waste Collection and Tranmentioning

confidence: 99%

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A Chance-Constrained Vehicle Routing Problem for Wet Waste Collection and Transportation Considering Carbon Emissions

Tao

Qiao

et al. 2020

IJERPH

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In order to solve the optimization problem of wet waste collection and transportation in Chinese cities, this paper constructs a chance-constrained low-carbon vehicle routing problem (CCLCVRP) model in waste management system and applies certain algorithms to solve the model. Considering the environmental protection point of view, the CCLCVRP model combines carbon emission costs with traditional waste management costs under the scenario of application of smart bins. Taking into the uncertainty of the waste generation rate, chance-constrained programming is applied to transform the uncertain model to a certain one. The initial optimal solution of this model is obtained by a proposed hybrid algorithm, that is, particle swarm optimization (PSO); and then the further optimized solution is obtained by simulated annealing (SA) algorithm, due to its global optimization capability. The effectiveness of PSOSA algorithm is verified by the classic database in a capacitated vehicle routing problem (CVRP). What’s more, a case of waste collection and transportation is applied in the model for acquiring reliable conclusions, and the application of the model is tested by setting different waste fill levels (WFLs) and credibility levels. The results show that total costs rise with the increase of credibility level reflecting dispatcher’s risk preference; the WFL value range between 0.65 and 0.75 can obtain the optimal solution under different credibility levels. Finally, according to these results, some constructive proposals are propounded for the government and the logistics organization dealing with waste collection and transportation.

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Section: Experimental Results Of Wfls and Credibility Levelsmentioning

confidence: 99%

“…Total collected waste NO.o f vehicles × Capacity o f vehicles (28) Unit Cost = Total cost Total collected waste…”

Section: Experimental Results Of Wfls and Credibility Levelsmentioning

confidence: 99%

Section: Research About Chance-constrained Programmingmentioning

confidence: 99%

Section: Research About Some Algorithms For Waste Collection and Tranmentioning

confidence: 99%

See 2 more Smart Citations

A Chance-Constrained Vehicle Routing Problem for Wet Waste Collection and Transportation Considering Carbon Emissions

Tao

Qiao

et al. 2020

IJERPH

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show abstract

“…Similarly, the efficiency of HEA are compared with the counterparts of HMOEA and LSMOVRPTW. Due to the stochasticity of the heuristics, the algorithm performs very well as it can be concluded from the average quality of the results [12]. Thus, this work records the running time of 3 algorithms on 27 instances.…”

Section: Computational Resultsmentioning

confidence: 99%

Robust multi‐objective vehicle routing problem with time windows for hazardous materials transportation

Men

Jiang

et al. 2020

IET intell. transp. syst

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Solving the time capacitated arc routing problem under fuzzy and stochastic travel and service times

et al. 2023

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Stochastic, as well as fuzzy uncertainty, can be found in most real‐world systems. Considering both types of uncertainties simultaneously makes optimization problems incredibly challenging. In this paper we propose a fuzzy simheuristic to solve the Time Capacitated Arc Routing Problem (TCARP) when the nature of the travel time can either be deterministic, stochastic or fuzzy. The main goal is to find a solution (vehicle routes) that minimizes the total time spent in servicing the required arcs. However, due to uncertainty, other characteristics of the solution are also considered. In particular, we illustrate how reliability concepts can enrich the probabilistic information given to decision‐makers. In order to solve the aforementioned optimization problem, we extend the concept of simheuristic framework so it can also include fuzzy elements. Hence, both stochastic and fuzzy uncertainty are simultaneously incorporated into the CARP. In order to test our approach, classical CARP instances have been adapted and extended so that customers' demands become either stochastic or fuzzy. The experimental results show the effectiveness of the proposed approach when compared with more traditional ones. In particular, our fuzzy simheuristic is capable of generating new best‐known solutions for the stochastic versions of some instances belonging to the tegl, tcarp, val, and rural benchmarks.

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A chance constrained programming approach for HazMat capacitated vehicle routing problem in Type-2 fuzzy environment

Cited by 44 publications

References 27 publications

A Chance-Constrained Vehicle Routing Problem for Wet Waste Collection and Transportation Considering Carbon Emissions

A Chance-Constrained Vehicle Routing Problem for Wet Waste Collection and Transportation Considering Carbon Emissions

Robust multi‐objective vehicle routing problem with time windows for hazardous materials transportation

Solving the time capacitated arc routing problem under fuzzy and stochastic travel and service times

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