A robust periodic capacitated arc routing problem for urban waste collection considering drivers and crew’s working time

Tirkolaee, Erfan Babaee; Mahdavi, Iraj; Esfahani, Mir Mehdi Seyyed

doi:10.1016/j.wasman.2018.03.015

Cited by 109 publications

(58 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Robust optimization approach has been studied by many researchers as an effective method to overcome the real‐world instability . This technique can efficiently control the uncertainty level and yield feasible solutions with a high probability …”

Section: Problem Definitionmentioning

confidence: 99%

“…Robust optimization approach has been studied by many researchers as an effective method to overcome the real-world instability. [37][38][39][40][41][42][43][44] This technique can efficiently control the uncertainty level and yield feasible solutions with a high probability. 45 For a brief description, the robust optimization approach suggested by Bertsimas and Sim 45 is presented as follows.…”

Section: Robust Modelmentioning

confidence: 99%

“…These deviations are calculated asĉ = c and̂i j = ′ ij , where and ′ are the uncertainty levels. Problem (40) can be rewritten as follows:…”

Section: Robust Modelmentioning

confidence: 99%

See 2 more Smart Citations

A robust green traffic‐based routing problem for perishable products distribution

Tirkolaee

Hadian

Weber

et al. 2019

Computational Intelligence

Self Cite

View full text Add to dashboard Cite

Nowadays, transportation and logistics are considered as the drivers of economic development in the countries due to their impacts on the main variables of the country's economy such as production, employment, price, and the cost of living. Statistics indicate that fuel consumption constructs a major part of transportation costs, where its optimization leads to the creation of an energy‐efficient and sustainable transportation system. On the other hand, vehicles' traffic is also one of the main criteria affecting the travel time of vehicles between demand nodes in a supply chain, increasing fuel consumption, and, consequently, damaging effects of greenhouse gasses. In this paper, a novel robust mixed‐integer linear programming model is developed for a green vehicle routing problem with intermediate depots considering different urban traffic conditions, fuel consumption, time windows of services, and uncertain demand for perishable products. To validate and solve the suggested model, CPLEX solver of GAMS software is employed as an exact method. Finally, a case study problem is investigated to evaluate the applicability of the proposed model and determine the optimal managerial insights and policies in the real‐world conditions using sensitivity analyses. Moreover, a novel robustness threshold comparison is conducted to find the optimal level of budget assignment.

show abstract

Section: Problem Definitionmentioning

confidence: 99%

Section: Robust Modelmentioning

confidence: 99%

See 1 more Smart Citation

A robust green traffic‐based routing problem for perishable products distribution

Tirkolaee

Hadian

Weber

et al. 2019

Computational Intelligence

Self Cite

View full text Add to dashboard Cite

show abstract

“…Tirkolaee et al [19] proposed a novel mathematical model for the robust PCARP considering working time of the vehicles. They developed a hybrid SA algorithm in order to solve the problem approximately.…”

Section: Introductionmentioning

confidence: 99%

“…The G-VRP was mainly studied since 2006 [19]. Lin et al [20] presented a review research in the field of G-VRP and its past and future trends.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Genetic Algorithm for Multi-Trip Green Capacitated Arc Routing Problem in the Scope of Urban Services

et al. 2018

View full text Add to dashboard Cite

Greenhouse gases (GHG) are the main reason for the global warming during the past decades. On the other hand, establishing a well-structured transportation system will yield to create least cost-pollution. This paper addresses a novel model for the multi-trip Green Capacitated Arc Routing Problem (G-CARP) with the aim of minimizing total cost including the cost of generation and emission of greenhouse gases, the cost of vehicle usage and routing cost. The cost of generation and emission of greenhouse gases is based on the calculation of the amount of carbon dioxide emitted from vehicles, which depends on such factors as the vehicle speed, weather conditions, load on the vehicle and traveled distance. The main applications of this problem are in municipalities for urban waste collection, road surface marking and so forth. Due to NP-hardness of the problem, a Hybrid Genetic Algorithm (HGA) is developed, wherein a heuristic and simulated annealing algorithm are applied to generate initial solutions and a Genetic Algorithm (GA) is then used to generate the best possible solution. The obtained numerical results indicate that the proposed algorithm could present desirable performance within a suitable computational run time. Finally, a sensitivity analysis is implemented on the maximum available time of the vehicles in order to determine the optimal policy.

show abstract

The vehicle routing programming of municipal solid waste collection under cognitive uncertainty

Wang,

Huo,

Lam

2024

Transp. j.

View full text Add to dashboard Cite

The rapid development of online shopping has led to an increase in express parcels, thus the proliferation of solid waste from parcel packaging. There are many other phenomena that have arisen with rapid economic development that also led to the surge in municipal solid waste. It is urgent to pay attention to municipal solid waste collection. Unexpected disruptive events lead to cognitive uncertainty and cause municipal waste collection to fail to function properly. This article studies how to properly carry out vehicle planning to achieve the shortest driving distance under cognitive uncertainty. The community's time window and the amount of garbage in each community are taken as uncertain variables. Based on the uncertainty theory, an uncertain vehicle routing problem (VRP) model and an uncertain VRP with the loading constraint model are constructed, and the solution algorithms of these two models are given. Several applications are carried out to evaluate the effectiveness of the proposed models and algorithms. This article proposes for the first time the models and algorithms to study the VRP under cognitive uncertainty. The findings draw important practical implications for adjusting municipal solid waste collection planning and logistics during disruptive events.

show abstract

A robust periodic capacitated arc routing problem for urban waste collection considering drivers and crew’s working time

Cited by 109 publications

References 18 publications

A robust green traffic‐based routing problem for perishable products distribution

A robust green traffic‐based routing problem for perishable products distribution

A Hybrid Genetic Algorithm for Multi-Trip Green Capacitated Arc Routing Problem in the Scope of Urban Services

The vehicle routing programming of municipal solid waste collection under cognitive uncertainty

Contact Info

Product

Resources

About