A probabilistic granular tabu search for the distance constrained capacitated vehicle routing problem

Bernal, José; Escobar, John Willmer; Paz, Juan Camilo; Linfati, Rodrigo; Gatica, Gustavo

doi:10.1504/ijise.2018.094267

Cited by 19 publications

(21 citation statements)

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“…The detailed explanation of Fig. 1 is as follows: distance-constrained capacitated vehicle routing problem -DCCVPR [6]; vehicle routing problem with backhauls -VRPB [7]; vehicle routing problem with time window -VRPTW [8], vehicle routing problem with pickup and delivery -VRPPD [9]; vehicle routing problem with backhauls and time window -VRPBTW [10]; vehicle routing problem with pickup and delivery and time window -VRPPDTW [11] In the above vehicle routing problems, the demands of the given transport network are deterministic, i.e. known in advance.…”

Section: Fig 1 Basic Vehicle Routing Problems and Their Relationsmentioning

confidence: 99%

“…Using the Ch-C conditions one can assure that the amount of collected waste on the route is smaller than the vehicle capacity with known probability (P) as shown in constraint (5). The capacity constraint (6) shows that the vehicle load never exceeds the vehicle capacity. Furthermore, Q is the maximum capacity of the vehicle, while q ij is the capacity of the vehicle after visiting node i, and before visiting node j.…”

Section: The Chance-constrained Model Of the Cvrpsdmentioning

confidence: 99%

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The Vehicle Routing Problem With Stochastic Demands in an Urban Area – A Case Study

Marković¹,

Petrovć²,

Ćojbašić³

et al. 2020

FU Mech Eng

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The vehicle routing problem with stochastic demands (VRPSD) is a combinatorial optimization problem. The VRPSD looks for vehicle routes to connect all customers with a depot, so that the total distance is minimized, each customer visited once by one vehicle, every route starts and ends at a depot, and the travelled distance and capacity of each vehicle are less than or equal to the given maximum value. Contrary to the classical VRP, in the VRPSD the demand in a node is known only after a vehicle arrives at the very node. This means that the vehicle routes are designed in uncertain conditions. This paper presents a heuristic and meta-heuristic approach for solving the VRPSD and discusses the real problem of municipal waste collection in the City of Niš.

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Section: Fig 1 Basic Vehicle Routing Problems and Their Relationsmentioning

confidence: 99%

Section: The Chance-constrained Model Of the Cvrpsdmentioning

confidence: 99%

The Vehicle Routing Problem With Stochastic Demands in an Urban Area – A Case Study

Marković¹,

Petrovć²,

Ćojbašić³

et al. 2020

FU Mech Eng

View full text Add to dashboard Cite

show abstract

“…The solution of the VRP problem must specify the customers to be assigned to each vehicle and the order of the customers to be visited to minimize the total cost subject to a variety of constraints, such as vehicle capacity and dispatch times [5,13,14]. Similar related routing problems have been studied by Michalos et al, [15], Escobar et al, [9], Escobar et al, [10], and Bernal-Moyano et al [16].…”

Section: State Of the Artmentioning

confidence: 99%

“…The considered problem is closely related to the well-known VRP, which is regarded as a nondeterministic polynomialtime NP-hard problem [3][4][5]. The operation costs for vehicle routing problems can be reduced between 10% and 20% using operational research techniques to facilitate planning [6][7][8][9][10].…”

Section: State Of the Artmentioning

confidence: 99%

“…The VRP is one of the most investigated combinatorial optimization problems [5,11] due to its mathematical complexity, its importance in daily situations, and its relevance to any organization that provides home delivery of a product or service. The VRP can be considered a general category of a set of problems with a set of geographically dispersed customers for which the demand of products or services must be satisfied by a fleet of vehicles departing from one or more depots [12].…”

Section: State Of the Artmentioning

confidence: 99%

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A Two-Phase Heuristic Algorithm for the Problem of Scheduling and Vehicle Routing for Delivery of Medication to Patients

Linfati

Escobar

Escalona

2018

Mathematical Problems in Engineering

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In this paper, a two-phase hybrid algorithm to address the problem of scheduling visits to customers and the vehicle routing problem of medication delivery to highly dependent patients is proposed. In the first phase, the issue of daily scheduling for a cluster of customers is solved via a flexible mathematical optimization model applied to different scenarios. The solution obtained in the first phase generates n clusters of patients and a frequency routing problem that considers delivery periodicity, location, demand, service times, travel times, and daily load-balancing constraints. In the second phase, a hybrid metaheuristic approach including the synergy and constant iteration between simulated annealing and a record-to-record algorithm is applied to improve the initial solution obtained in the first phase. The effectiveness of the proposed algorithm is validated with real data obtained from a pilot project in Chile. The results are promising and demonstrate the efficiency of the proposed methodology.

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Advertising through UAVs: Optimized path system for delivering smart real‐estate advertisement materials

Ullah

Al‐Turjman²,

Qayyum

et al. 2021

Int J Intell Syst

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Real-estate advertisements through electronic and print media are bringing considerable fortune to the global real-estate sector. However, innovative advertisement methods must be adopted if real estate aims to transform into smart real estate. The current study, which is based on a systematic literature review of 58 articles published in the last decade, identifies key media for real-estate advertisements as print media (e.g., magazines, brochures, newspapers, and digests), electronic media (e.g., websites, social media, and other digital tools), and mixed methods (e.g., billboards, signs and banners, and personalized messaging). This study takes the case of Kingsford suburb in the eastern Sydney area, and investigates the performance of the Australian real-estate industry in general and lists the key dynamics of properties in Kingsford and its prominent real-estate agencies. An unmanned aerial vehicle (UAV)-based smart real-estate advertisement material delivery system is proposed to deliver advertisement materials and gifts to the potential customers of these agencies. The system paths are optimized through four Java-run algorithms: greedy, interroute, intraroute, and Tabu. Results based on six cases, three each for rent and sales with varying numbers of customers and UAVs and an 8-h operating time, indicate that the Tabu algorithm provides the best-optimized paths in all cases, followed by the interroute, intraroute, and greedy algorithms. However, the inter-and intraroute algorithms show superior performance in terms of computation speed. The proposed framework is a practical approach in disrupting the real-estate advertising sector, thereby helping this sector transform into a smart real estate consistent with industry 4.0 goals.

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A probabilistic granular tabu search for the distance constrained capacitated vehicle routing problem

Cited by 19 publications

References 0 publications

The Vehicle Routing Problem With Stochastic Demands in an Urban Area – A Case Study

The Vehicle Routing Problem With Stochastic Demands in an Urban Area – A Case Study

A Two-Phase Heuristic Algorithm for the Problem of Scheduling and Vehicle Routing for Delivery of Medication to Patients

Advertising through UAVs: Optimized path system for delivering smart real‐estate advertisement materials

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