Solving a multi-objective location routing problem for infectious waste disposal using hybrid goal programming and hybrid genetic algorithm

Wichapa, Narong; Khokhajaikiat, Porntep

doi:10.5267/j.ijiec.2017.4.003

Cited by 27 publications

(18 citation statements)

References 44 publications

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“…Tirkolaee et al [11] designed an improved ant colony algorithm for the proposed model of a capacitated arc routing problem (CARP). Wichapa and Khokhajaikia [48] designed hybrid genetic algorithm (HGA) to solve VRP for infectious waste transportation. Delgado-Antequera et al [34] proposed an integrated greedy algorithm coupled with a variable neighborhood search for a multi-objective routing problem for waste collection and transportation.…”

Section: Research About Algorithmsmentioning

confidence: 99%

Optimization of Vehicle Routing for Waste Collection and Transportation

Tao

Yang

2020

IJERPH

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For the sake of solving the optimization problem of urban waste collection and transportation in China, a priority considered green vehicle routing problem (PCGVRP) model in a waste management system is constructed in this paper, and specific algorithms are designed to solve the model. We pay particular concern to the possibility of immediate waste collection services for high-priority waste bins, e.g., those containing hospital or medical waste, because the harmful waste needs to be collected immediately. Otherwise, these may cause dangerous or negative effects. From the perspective of environmental protection, the proposed PCGVRP model considers both greenhouse gas (GHG) emission costs and conventional waste management costs. Waste filling level (WFL) is considered with the deployment of sensors on waste bins to realize dynamic routes instead of fixed routes, so that the economy and efficiency of waste collection and transportation can be improved. The optimal solution is obtained by a local search hybrid algorithm (LSHA), that is, the initial optimal solution is obtained by particle swarm optimization (PSO) and then a local search is performed on the initial optimal solution, which will be optimized by a simulated annealing (SA) algorithm by virtue of the global search capability. Several instances are selected from the database of capacitated vehicle routing problem (CVRP) so as to test and verify the effectiveness of the proposed LSHA algorithm. In addition, to obtain credible results and conclusions, a case using data about waste collection and transportation is employed to verify the PCGVRP model, and the effectiveness and practicability of the model was tested by setting a series of values of bins’ number with high priority and WFLs. The results show that (1) the proposed model can achieve a 42.3% reduction of negative effect compared with the traditional one; (2) a certain value of WFL between 60% and 80% can realize high efficiency of the waste collection and transportation; and (3) the best specific value of WFL is determined by the number of waste bins with high priority. Finally, some constructive propositions are put forward for the Environmental Protection Administration and waste management institutions based on these conclusions.

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Section: Research About Algorithmsmentioning

confidence: 99%

Optimization of Vehicle Routing for Waste Collection and Transportation

Tao

Yang

2020

IJERPH

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“…To find solutions to their model, they used two meta -heuristics, namely the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) algorithm. Wichapa and Khokhajaikiat (2018) focused on the location routing problem for the disposal of infectious wastes. They developed a hybrid approach consisting of the AHP, Genetic Algorithm (GA), and Goal Programming (GP) method.…”

Section: Related Workmentioning

confidence: 99%

A healthcare logistic network considering stochastic emission of contamination: Bi-objective model and solution algorithm

Nikzamir

Baradaran

2020

Transportation Research Part E: Logistics and Transportation Re

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Highlights A novel healthcare waste location-routing problem is developed with a new perspective in healthcare logistics networks. A stochastic essence for the emission of contamination is considered. The management of medical wastes in Coronavirus Disease 2019 is focused. A real case study is modeled to manage the logistics of infectious and non-infectious healthcare wastes. A Multi-Objective Water-Flow like Algorithm with novel operators is developed and compared with the others.

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“…There are a lot of real-world problems which are very hard to tackle using exact methods. The Vehicle Routing Problem (VRP), which is famous as an NP-hard problem, is a well-known problem in operations research and combinatorial optimization (Chokanat et al, 2019;Wichapa & Khokhajaikiat, 2018). Much attention of researchers has been devoted on the development of the characteristics of the problem and assumptions, leading to an enormous number of VRPs and variants, as well as various heuristic/metaheuristic modifications to tackle the problem (Hanum et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

A novel two-phase approach for solving the multi-compartment vehicle routing problem with a heterogeneous fleet of vehicles: a case study on fuel delivery

Chowmali¹,

Sukto²

2020

10.5267/j.dsl

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Distribution of goods is one of the main issues that directly affect the performance of the companies since efficient distribution of goods saves energy costs and also leads to reduced environmental impact. The multi-compartment vehicle routing problem (MCVRP) with a heterogeneous fleet of vehicles is encountered when dealing with this situation in many practical cases. This paper is motivated by the fuel delivery problem where the main objective of this research is to minimize the total driving distance using a minimum number of vehicles. Based on a case study of twenty petrol stations in northeastern Thailand, a novel two-phase heuristic, which is a variant of the Fisher and Jaikumar Algorithm (FJA), is proposed. The study first formulates an MCVRP model and then a mixed-integer linear programming (MILP) model is formulated for selecting the numbers and types of vehicles. A new clustering-based model is also developed in order to select the seed nodes and all customer nodes are considered as candidate seed nodes. The new Generalized Assignment Problem model (GAP model) is formulated to allocate the customers into each cluster. Finally, based on the traveling salesman problem (TSP), each cluster is solved in order to minimize the total driving distance. Numerical results show that the proposed heuristic is effective for solving the proposed model. The proposed algorithm can be used to minimize the total driving distance and the number of vehicles of the distribution network for fuel delivery.

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Solving a multi-objective location routing problem for infectious waste disposal using hybrid goal programming and hybrid genetic algorithm

Cited by 27 publications

References 44 publications

Optimization of Vehicle Routing for Waste Collection and Transportation

Optimization of Vehicle Routing for Waste Collection and Transportation

A healthcare logistic network considering stochastic emission of contamination: Bi-objective model and solution algorithm

A novel two-phase approach for solving the multi-compartment vehicle routing problem with a heterogeneous fleet of vehicles: a case study on fuel delivery

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