Stochastic single vehicle routing problem with delivery and pick up and a predefined customer sequence

Minis, Ioannis; Tatarakis, Antonios

doi:10.1016/j.ejor.2011.03.011

Cited by 36 publications

(10 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, multiple vehicles, vehicle capacities, tour-length restrictions, and delivery and pickup time windows among others complicate the planning of transportation and distribution operations in global logistics network . Analytics methodologies and techniques are used to optimize the routing of goods, vehicles, as well as crew (Novoa and Stoner, 2009;Lei et al, 2011;Minis and Tatarakis, 2011) in order to balance between transportation costs and margins, and pay attention to maintenance and safety.…”

Section: Logisticsmentioning

confidence: 99%

Big data analytics in logistics and supply chain management: Certain investigations for research and applications

Wang

Gunasekaran

Ngai

et al. 2016

International Journal of Production Economics

1,115

750

View full text Add to dashboard Cite

The amount of data produced and communicated over the Internet is significantly increasing, thereby creating challenges for the organizations that would like to reap the benefits from analyzing this massive influx of big data. This is because big data can provide unique insights into, inter alia, market trends, customer buying patterns, and maintenance cycles, as well as into ways of lowering costs and enabling more targeted business decisions. Realizing the importance of big data business analytics (BDBA), we review and classify the literature on the application of BDBA on logistics and supply chain management (LSCM) -that we define as supply chain analytics (SCA), based on the nature of analytics (descriptive, predictive, prescriptive) and the focus of the LSCM (strategy and operations). To assess the extent to which SCA is applied within LSCM, we propose a maturity framework of SCA, based on four capability levels, that is, functional, process-based, collaborative, agile SCA, and sustainable SCA. We highlight the role of SCA in LSCM and denote the use of methodologies and techniques to collect, disseminate, analyze, and use big data driven information. Furthermore, we stress the need for managers to understand BDBA and SCA as strategic assets that should be integrated across business activities to enable integrated enterprise business analytics. Finally, we outline the limitations of our study and future research directions.

show abstract

Section: Logisticsmentioning

confidence: 99%

Big data analytics in logistics and supply chain management: Certain investigations for research and applications

Wang

Gunasekaran

Ngai

et al. 2016

International Journal of Production Economics

1,115

750

View full text Add to dashboard Cite

show abstract

“…The following methods were found: branch and cut algorithm (5 papers) [14][15][16][17][18]; branch and price algorithm (2 papers) [19,20]; branch and bound algorithm (1 paper), [21] dynamic programming (5 papers) [22][23][24][25][26]; mixed integer linear programming (5 papers) [27][28][29][30][31]; experiments (1 paper) [32]; column generation scheme (4 papers) [33][34][35][36]; classical theory of programming and graph theory (1 paper) [37].…”

Section: Exact Methodsmentioning

confidence: 99%

Description of the classification of publications and the models used in solving of the vehicle routing problem with pickup and delivery

Silva

Zuluaga

2016

Rev. ing. univ. Medellín

View full text Add to dashboard Cite

This review paper presents the description of the state of the art of the vehicle routing problem with pickups and deliveries, vrppd, product obtained from the literature review of most of the models reported in the international technical literature and used for many years by specialized researchers in the field. This classification considers the different solution methods, the treatment of the problem in time and future trends in its formulation, and proposal of new methods of solution, such as the metaheuristics caused by the complexity of the problem. Finally, several elements are left to discuss about existing and available tools for solving this problem.

show abstract

“…There are many kinds of VRPs, including MDVRP [II,12], VRPTW [13][14][15], VRP PD [17][18], CVRP (Capacity VRP) [19], etc. [12].…”

Section: Relative Workmentioning

confidence: 99%

“…redefine users' sequence to solve the problem[18].The above researchers put forward their respecti ve solutions to different types of VRP problems. Nevertheless, their methods can only apply to a single scenario.…”

mentioning

confidence: 99%

A Vehicle Routing Problem based on intelligent batteries transfer management for the EV network

Xia

Cheng

2014

China Commun.

View full text Add to dashboard Cite

Batteries transfer management is one important aspect in electric vehicle (EV) network's intelligent operation management system. Batteries transfer is a special and much more complex VRP (Vehicle Routing Problem) which takes the multiple constraints such as dynamic multi-depots, time windows, simultaneous pickups and deliveries, distance minimization, etc. into account. We call it VRPEVB (VRP with EV Batteries). This paper, based on the intelligent management model of EV's battery power, puts forward a battery transfer algorithm for the EV network which considers the traffic congestion that changes dynamically and uses improved Ant Colony Optimization. By setting a reasonable tabv range, special update rules of the pheromone and path list memory functions, the algorithm can have a better convergence, and its feasibility is proved by the experiment in an EV's demonstration operation system. Keywords: VRP; battery; power management; ant colony algorithm; electric vehicle network This paper, based on the intelligent man agement model of EV's battery power, puts forward a battery transfer algorithm for the EV network which considers the traffic congestion that changes dynamically and uses improved Ant Colony Optimiza tion.

show abstract

Stochastic single vehicle routing problem with delivery and pick up and a predefined customer sequence

Cited by 36 publications

References 12 publications

Big data analytics in logistics and supply chain management: Certain investigations for research and applications

Big data analytics in logistics and supply chain management: Certain investigations for research and applications

Description of the classification of publications and the models used in solving of the vehicle routing problem with pickup and delivery

A Vehicle Routing Problem based on intelligent batteries transfer management for the EV network

Contact Info

Product

Resources

About