Multi-objective optimization of a two-echelon vehicle routing problem with vehicle synchronization and ‘grey zone’ customers arising in urban logistics

Anderluh, Alexandra; Nolz, Pamela C.; Hemmelmayr, Vera C.; Crainic, Teodor Gabriel

doi:10.1016/j.ejor.2019.07.049

Cited by 83 publications

(36 citation statements)

References 38 publications

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“…Moreover, a real-world case study was analyzed in Sari of Iran to assess the performance of the model, and eventually, numerous sensitivity analyses were accomplished to analyze the behavior of the objective functions. Anderluh et al (2019) attempted to simulate different scenarios in the duration of the trip and carried out a solution in this context. The computational conclusions indicate that the rate of synchronization is straightly associated with the possible advancements with the reuse of the program.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization and incorporating of green traffic for dynamic vehicle routing problem with perishable products

Talouki

Javadian

Movahedi

2021

Environ Sci Pollut Res

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In view of the significance of transportation management and logistics in the economic concept and raising the productivity of production systems, well-timed procurement of perishable materials and goods is determined as a pivotal prerequisite for economic and environmental development. Since the perishable goods produced must be made delivered to consumers as early as possible on account of the limited lifespan, thus, the vulnerability of these products is extremely high, owing to the high cost of transportation as well as the environmental impacts. So that solves this problem, this study represents a problem of dynamic green vehicle routing of perishable products in green traffic conditions that optimizes the total cost for a dynamic transportation network and minimizes environmental influences, and increases customer satisfaction. The introduced model is implemented in light of time windows as a trustworthy solution for monitoring the dynamic logistics process and attaining instantaneous information on the basis of the green traffic situation and travel duration, which is commonly known by the Logit function. Assuming the three-objective programming model, we consider a new improved algorithm developed for a novel augmented ε-constraint heuristic approach. Furthermore, robust optimization has been conducted for the established problem to tackle with uncertainties. Uncertainties are included demand and economic parameters. Eventually, to validate the proposed model, a case study was carried out at Kaleh Amol Dairy Company in Iran. The conclusions of sensitivity analysis by implementing the model in the real world indicate that the model and approach presented in various uncertainty scenarios have high flexibility.

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Section: Literature Reviewmentioning

confidence: 99%

Optimization and incorporating of green traffic for dynamic vehicle routing problem with perishable products

Talouki

Javadian

Movahedi

2021

Environ Sci Pollut Res

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“…(1) Objective function (1) aims to minimize the distribution cost, including the effective transport cost and penalty; Constraint (2) means the mean customer satisfaction must be greater than or equal to the given value of β; Constraint (3) means the number of vehicles leaving the distribution center should not surpass k; Constraint (4) means all vehicles leaving the distribution center must return to the center; Constraints (5) and (6) mean that each vehicle can only serve each customer once; Constraint (7) means the quantity of products loaded onto a vehicle should not surpass the loading capacity of the vehicle; Constraint (8) means the time window required by each customer; Constraint (9) means the value range of xijk; Constraint (10) means the travel time from customer i to customer j; Constraint (11) means the travel time from the distribution center to customer i; Constraint (12) means the penalty for the delivery beyond the time window; Constraint (13) means the degree of satisfaction of customer i with different arrival times ti.…”

Section: Model Constructionmentioning

confidence: 99%

“…Therefore, these algorithms have been combined into hybrid algorithms to fully exert their complementary advantages. The hybrid algorithms include SA-GA, GA-PSO, ACA-PSO, etc [5][6][7]. This sub-section selects the SA-GA to solve the established VRPSTW model, in view of the features of the problem and the strengths of this hybrid algorithm.…”

Section: Model Optimization By Sa-gamentioning

confidence: 99%

“…To minimize the total cost of the collaborative multiple centers VRP (CMCVRP), Wang et al [4] designed an integer programming model that considers the effective transport cost in distribution centers (DC) and that of vehicles from each DC, and solved the model with a self-designed multi-phase hybrid algorithm, which combines the merits of clustering, dynamic planning, and heuristic algorithms. Considering vehicle synchronization and grey zone customers, Alexandra et al [5] constructed a multi-objective optimization model for two-level VRP in the context of urban freight deliveries.…”

Section: Introductionmentioning

confidence: 99%

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Collaborative Distribution in the Soft Time Window of Agricultural-Means Supply Chain Based on Simulated Annealing-Genetic Algorithm

Zhu¹,

Wang²,

Li³

2020

JESA

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This paper mainly explores the collaborative distribution to multiple customers at the terminal of agricultural-means supply chain (AMSC). Firstly, a cost optimization model for collaborative distribution constrained by time window was constructed based on fuzzy appointment time function. Next, the proposed model was solved by simulated annealing-genetic algorithm (SA-GA). Through a case study, the cost optimization model constrained by customer satisfaction was compared with that not constrained by customer satisfaction. The results show that the cost optimization model constrained by customer satisfaction made the customers more satisfied without greatly elevating the distribution cost. The research results shed new light on the collaborative distribution of time-sensitive agricultural-means (AM) products, and the management of the AMSC.

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“…The paper [15] deals with the routing issue to decrease the environmental and noise pollution in the first echelon through the Flow simulation product to generate a rational vehicle path. In the research [16], the routing problem consist in a vehicle assignment to serve the consumers in different echelons. М. Soysal et al [17] in routing problems.…”

Section: Literature Reviewmentioning

confidence: 99%

A Two-Echelon Green Supply Chain for Urban Delivery

et al. 2019

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In recent years the urbanization to affect many countries of the world has made the significant changes to the material flow at all levels of the supply chain. The last mile logistics operating in the urban area has also changed notably. An increase in the volume of material flow within cities has led to a growth in the number of deliveries and the freight turnover, accordingly. The above-stated processes greatly reduce the sustainability of cities, which while keeping the urbanization trend, can lead to the serious negative results of the social and environmental nature not only for the cities, but also for the countries. One way to solve this problem is to create the green supply chains from the multi-echeloning principles. In the paper, the authors have presented a two-echelon green supply chain using the zero transport emissions within the second echelon. A multi-criteria function has been developed to assess the rational location of a transfer point in order to reduce the negative environmental impact from the transportation system. With the PTV Visum software product, a simulation has been conducted to evaluate the alternative scenarios for generating a green supply chain.

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Multi-objective optimization of a two-echelon vehicle routing problem with vehicle synchronization and ‘grey zone’ customers arising in urban logistics

Cited by 83 publications

References 38 publications

Optimization and incorporating of green traffic for dynamic vehicle routing problem with perishable products

Optimization and incorporating of green traffic for dynamic vehicle routing problem with perishable products

Collaborative Distribution in the Soft Time Window of Agricultural-Means Supply Chain Based on Simulated Annealing-Genetic Algorithm

A Two-Echelon Green Supply Chain for Urban Delivery

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