Multi-depot multi-trip vehicle routing problem with time windows and release dates

Zhen, Lu; Ma, Chengle; Wang, Kai; Xiao, Liyang; Zhang, Wei

doi:10.1016/j.tre.2020.101866

Cited by 130 publications

(53 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In (Zhen et al, 2020), the authors have investigated the MDVRP with respect to the practical scenario in a last mile distribution operation. The authors express the design of a set of trips for the fleet of vehicles where there are several depots for minimizing the total travelling time.…”

Section: Exact Methodsmentioning

confidence: 99%

Five years of multi-depot vehicle routing problems

Jayarathna¹,

Lanel

Juman

2020

J. sustain. dev. transp. logist.

View full text Add to dashboard Cite

show abstract

Section: Exact Methodsmentioning

confidence: 99%

Five years of multi-depot vehicle routing problems

Jayarathna¹,

Lanel

Juman

2020

J. sustain. dev. transp. logist.

View full text Add to dashboard Cite

show abstract

“…Three steps have been described in details in order to find near optimal solution of the real-life case study problem in the following subsections. Therefore, the first step is based on a well-known algorithm CWS, which was proposed in (23) to generate a feasible initial solution for VRPTW. In the second step, we applied the ALNS algorithm and IG in the solution obtained in the first step in a parallel way.…”

Section: Methodsmentioning

confidence: 99%

Solving practical waste collection with time windows in an urban area

Almutairi

2020

IJASP

View full text Add to dashboard Cite

In logistics, several algorithms can be implemented in order to solve the problems of the vehicle routing with variants in order to find near-optimal solutions. Waste Collection can be considered as an essential logistic activity within any area or city. This kind of paper is aimed to implement Iterated greedy (IG) and Adaptive Large Neighborhood Search (ALNS) to solve waste collection vehicle routing problem with time windows on a real-case study. The idea is to generate an efficient way to collect waste problems in an area located in Riyadh, Saudi Arabia. Moreover, generating a route plays a significant role in terms of serving all customers’ demands who have own different time windows of receiving goods. Also, the performance of the proposed algorithms according to all instances is examined and minimizing the total costs and meeting all constraints that related to capacity, time windows, and others. To evaluate the execution of the presented algorithms, the computational results showed essential improvements, and also ALNS algorithm generates reasonable solutions in terms of total costs and a reasonable amount of time, when compared to other algorithms.

show abstract

“…Constraints (18) ensure that there are no subpaths in vehicle loop. Constraints (19) and (20) limit the range of decision variables.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…Particle swarm optimization (PSO) has been studied extensively since it was proposed [17]. As one of the swarm intelligence algorithms, PSO has been widely used in vehicle routing problem in the past few years, for example, vehicle routing problem with multiple pickup and delivery [18] and multidepot multitrip vehicle routing problem [19].…”

Section: Particle Swarm Optimization (Pso)mentioning

confidence: 99%

Multidepot Heterogeneous Vehicle Routing Problem for a Variety of Hazardous Materials with Risk Analysis

Wang¹,

Qian

Tan

et al. 2020

Scientific Programming

View full text Add to dashboard Cite

This study investigates a multidepot heterogeneous vehicle routing problem for a variety of hazardous materials with risk analysis, which is a practical problem in the actual industrial field. The objective of the problem is to design a series of routes that minimize the total cost composed of transportation cost, risk cost, and overtime work cost. Comprehensive consideration of factors such as transportation costs, multiple depots, heterogeneous vehicles, risks, and multiple accident scenarios is involved in our study. The problem is defined as a mixed integer programming model. A bidirectional tuning heuristic algorithm and particle swarm optimization algorithm are developed to solve the problem of different scales of instances. Computational results are competitive such that our algorithm can obtain effective results in small-scale instances and show great efficiency in large-scale instances with 70 customers, 30 vehicles, and 3 types of hazardous materials.

show abstract

Multi-depot multi-trip vehicle routing problem with time windows and release dates

Cited by 130 publications

References 30 publications

Five years of multi-depot vehicle routing problems

Five years of multi-depot vehicle routing problems

Solving practical waste collection with time windows in an urban area

Multidepot Heterogeneous Vehicle Routing Problem for a Variety of Hazardous Materials with Risk Analysis

Contact Info

Product

Resources

About