A Bee Evolutionary Algorithm for Multiobjective Vehicle Routing Problem with Simultaneous Pickup and Delivery

Gong, Guiliang; Deng, Qianwang; Gong, Xuran; Zhang, Like; Wang, Haibin; Xie, He

doi:10.1155/2018/2571380

Cited by 14 publications

(10 citation statements)

References 35 publications

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“…The main contribution lies in the use of cross-docking, which can be applied during loading, sorting or unloading. Gong et al (2018) treated the new closed-loop supply chain logistics network of the vehicle routing problem with simultaneous pickups and deliveries (VRPSPD) dominated by the remanufacturer, where they presented the bee evolutionary algorithm guiding nondominated sorting genetic algorithm II (BEG-NSGA-II) to solve it with three goals in mind: to minimize fuel consumption, minimize waiting time and minimize the distance to delivery. The problem was applied in the context of logistic distribution and generic tests were conducted.…”

Section: Correlated Workmentioning

confidence: 99%

“…The proposal for the Bi-objective Green Vehicle Routing Problem (BGVRP) presented here is to combine the VRP, MOO techniques and environmental considerations to generate economically and environmentally feasible routing. In this context, many researchers have adapted their solution procedures to attend to issues related to factors such as cost, travel time, CO2 emissions, fuel consumption, reverse logistics and environmental impacts (Lin, Choy, Ho, Chung, & Lam, 2014;Norouzi, Sadegh-Amalnick, & Tavakkoli-Moghaddam, 2017;Gong et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Uma nova abordagem para o problema de roteamento de veículos green bi-objetivo: otimização na distribuição de jornais

Ferreira

Steiner

2022

Exacta

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The purpose of this work is to present a methodology to provide a solution to a Bi-objective Green Vehicle Routing Problem (BGVRP). The methodology, illustrated using a case study (newspaper distribution problem) and instances from the literature, was divided into three stages: Stage 1, data treatment; Stage 2, metaheuristic approaches (hybrid or non-hybrid), used comparatively, and, Stage 3, analysis of the results, with a comparison of the algorithms. An optimization of 19.9% was achieved for Objective Function 1 (OF1; minimization of CO2 emissions) and consequently the same percentage for the minimization of total distance, and 87.5% for Objective Function 2 (OF2; minimization of the difference in demand). Metaheuristic approaches hybrid achieved superior results for case study and instances.

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Section: Correlated Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Uma nova abordagem para o problema de roteamento de veículos green bi-objetivo: otimização na distribuição de jornais

Ferreira

Steiner

2022

Exacta

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“…En las cadenas de suministro se viene trabajando fuertemente con los AG en el área de problemas de ruteo; tal es el caso de las investigaciones [27,28,29] que proponen sistemas de optimización de rutas internas para la ubicación y carga de los productos en almacenados en bodegas, permitiendo utilizar distintos tipos de vehículos de acuerdo al contexto, que conllevan a la reducción de costos y mejoramiento del servicio. Así mismo se han hecho propuestas para mejorar la entrega y recogida de productos, optimizando la asignación de vehículos respeto al lugar de residencia de los clientes [30,31,32] y la programación de los despachos de acuerdo a las órdenes de pedido [33,34,35].…”

Section: Algoritmos Genéticosunclassified

Oportunidades para la transformación digital de la cadena de suministro del sector bananero basado en software con inteligencia artificial

Palacio

2021

Rev. politec.

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La inteligencia artificial ofrece grandes oportunidades para la cadena de suministro, siendo esto una ventaja competitiva para el mercado cambiante de hoy en día. Este artículo tiene como objetivo identificar los impactos y oportunidades que puede ofrecer el software con inteligencia artificial para facilitar la operación y mejorar el desempeño de la cadena de suministro en el sector bananero de Colombia. La metodología de trabajo consta de seis pasos en donde se obtuvo un total de 72 investigaciones. Las fuentes de información fueron cuatro bases de datos. Como conclusión principal, la cadena de suministro del sector bananero tiene todo lo necesario para que se implementen soluciones basadas en software inteligente con el fin de lograr una adaptación, flexibilidad y sensibilidad al contexto y dominio de ejecución. Artificial intelligence offers great opportunities for the supply chain, making it a competitive advantage for today's changing market. This paper aims to identify the impacts and opportunities that artificial intelligence software can offer to supply chain in the Colombian banana sector to facilitate the operation and improve the performance. The searching method consists of six steps getting 72 investigations finally. The sources of information were four databases. The main conclusion is the supply chain of the banana sector has everything for implementation of solutions based on intelligent software in order to achieve adaptation, flexibility and context awarenes and execution domain.

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“…In Ref. [12], Gong et al studied the vehicle routing problem with simultaneous pickups and deliveries (VRPSPD) on a closed-loop supply chain logistics network. Three types of customers: distributors, recyclers, and suppliers taken into account.…”

Section: Literature Surveymentioning

confidence: 99%

Revenue Management Focused Capacitated Vehicle Routing Model in Supply Chain Management

Örnek¹

2020

IJST

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Objectives: To propose revenue management focused model for Capacitated Vehicle Routing Problem with Simultaneous Pickup and Delivery and pursue a solution to it. In some industries, customer demand for delivery and pickup fluctuates and the vehicle capacities are limited. Existing research focuses on either Revenue Maximization or Transportation Cost Minimization. To be able to run such businesses profitably, it is necessary to consider both objectives by the help of the proposed model. Dynamic pricing will be used for revenue maximization, by booking early reservations for a lower price. Vehicle Routing Problem will determine the route to minimize the total transportation cost. Methods: The capacitated vehicle routing model with simultaneous pickup and delivery is combined with a revenue management model in which low price early reservations are allowed. In case the customer orders cannot be handled with existing vehicle capacities, some of the early reservation orders are canceled and a cancellation fee is incurred. The model is solved with a mixed-integer linear programming (MILP) solver. Findings: The proposed model is tested against a real-world data set. The result shows that unprofitable customer orders are determined by the model and rejected despite there is a cancellation fee. By applying the revenue management model, it is observed that there is an increase in the total profit. Novelty: To the best of our knowledge, this study proposed a revenue management focused MILP model for VRP with simultaneous pickup and delivery for the first time.

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A Bee Evolutionary Algorithm for Multiobjective Vehicle Routing Problem with Simultaneous Pickup and Delivery

Cited by 14 publications

References 35 publications

Uma nova abordagem para o problema de roteamento de veículos green bi-objetivo: otimização na distribuição de jornais

Uma nova abordagem para o problema de roteamento de veículos green bi-objetivo: otimização na distribuição de jornais

Oportunidades para la transformación digital de la cadena de suministro del sector bananero basado en software con inteligencia artificial

Revenue Management Focused Capacitated Vehicle Routing Model in Supply Chain Management

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