The capacitated pollution routing problem with pickup and delivery in the last mile

2019 ◽  
Vol 31 (4) ◽  
pp. 1193-1215 ◽  
Author(s):  
Yuyang Tan ◽  
Lei Deng ◽  
Longxiao Li ◽  
Fang Yuan
Keyword(s):  
Real World ◽  
Distribution Model ◽  
Pickup And Delivery ◽  
Routing Problem ◽  
Actual Distribution ◽  
Content Type ◽  
Last Mile ◽  
Speed Optimization ◽  
Logistics Enterprises ◽  
Pollution Routing Problem

Purpose With the increasing awareness of global warming and the important role of last mile distribution in logistics activities, the purpose of this paper is to build an environmental and effective last mile distribution model considering fuel consumption and greenhouse gas emission, vehicle capacity and two practical delivery service options: home delivery (HD) and pickup site service (PS). This paper calls the problem as the capacitated pollution-routing problem with pickup and delivery (CPRPPD). The goal is to find an optimal route to minimize operational and environmental costs, as well as a set of optimal speeds over each arc, while respecting capacity constraints of vehicles and pickup sites. Design/methodology/approach To solve this problem, this research proposes a two-phase heuristic algorithm by combining a hybrid ant colony optimization (HACO) in the first stage and a multiple population genetic algorithm in the second stage. First, the HACO is presented to find the minimal route solution and reduce distribution cost based on optimizing the speed over each arc. Findings To verify the proposed CPRPPD model and algorithm, a real-world instance is conducted. Comparing with the scenario including HD service only, the scenario including both HD and PS option is more economical, which indicates that the CPRPPD model is more efficient. Besides, the results of speed optimization are significantly better than before. Practical implications The developed CPRPPD model not only minimizes delivery time and reduces the total emission cost, but also helps logistics enterprises to establish a more complete distribution system and increases customer satisfaction. The model and algorithm of this paper provide optimal support for the actual distribution activities of logistics enterprises in low-carbon environment, and also provide reference for the government to formulate energy-saving and emission reduction policies. Originality/value This paper provides a great space for the improvement of carbon emissions in the last mile distribution. The results show that the distribution arrangement including HD and PS services in the last mile adopting speed optimization can significantly reduce the carbon emission. Additionally, an integrated real-world instance is applied in this paper to illustrate the validity of the model and the effectiveness of this method.

Dynamic truck and trailer routing problem for last mile distribution in disaster response

2018 ◽  
Vol 8 (2) ◽  
pp. 252-278 ◽  
Author(s):  
Meilinda F.N. Maghfiroh ◽  
Shinya Hanaoka
Keyword(s):  
Vehicle Routing ◽  
Disaster Response ◽  
Distribution Systems ◽  
Simulated Annealing Algorithm ◽  
Distribution Model ◽  
Neighborhood Search ◽  
Dynamic Vehicle Routing ◽  
Routing Problem ◽  
Content Type ◽  
Last Mile

Purpose The purpose of this paper is to investigate the application of the dynamic vehicle routing problem for last mile distribution during disaster response. The authors explore a model that involves limited heterogeneous vehicles, multiple trips, locations with different accessibilities, uncertain demands, and anticipating new locations that are expected to build responsive last mile distribution systems. Design/methodology/approach The modified simulated annealing algorithm with variable neighborhood search for local search is used to solve the last mile distribution model based on the criterion of total travel time. A dynamic simulator that accommodates new requests from demand nodes and a sample average estimator was added to the framework to deal with the stochastic and dynamicity of the problem. Findings This study illustrates some practical complexities in last mile distribution during disaster response and shows the benefits of flexible vehicle routing by considering stochastic and dynamic situations. Research limitations/implications This study only focuses day-to-day distribution on road/land transportation for distribution, and additional transportation modes need to be considered further. Practical implications The proposed model offers operational insights for government disaster agencies by highlighting the dynamic model concept for supporting relief distribution decisions. The result suggests that different characteristics and complexities of affected areas might require different distribution strategies. Originality/value This study modifies the concept of the truck and trailer routing problem to model locations with different accessibilities while anticipating the information gap for demand size and locations. The results show the importance of flexible distribution systems during a disaster for minimizing the disaster risks.

A robust possibilistic programming model for production-routing problem in a three-echelon supply chain

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Ali Beheshtinia ◽  
Narjes Salmabadi ◽  
Somaye Rahimi
Keyword(s):  
Supply Chain ◽  
Real Life ◽  
Model Parameters ◽  
Pickup And Delivery ◽  
Distribution Centers ◽  
Routing Problem ◽  
Remarkable Feature ◽  
Content Type ◽  
Proposed Model ◽  
Production Routing

Purpose This paper aims to provide an integrated production-routing model in a three-echelon supply chain containing a two-layer transportation system to minimize the total costs of production, transportation, inventory holding and expired drugs treatment. In the proposed problem, some specifications such as multisite manufacturing, simultaneous pickup and delivery and uncertainty in parameters are considered. Design/methodology/approach At first, a mathematical model has been proposed for the problem. Then, one possibilistic model and one robust possibilistic model equivalent to the initial model are provided regarding the uncertain nature of the model parameters and the inaccessibility of their probability function. Finally, the performance of the proposed model is evaluated using the real data collected from a pharmaceutical production center in Iran. The results reveal the proper performance of the proposed models. Findings The results obtained from applying the proposed model to a real-life production center indicated that the number of expired drugs has decreased because of using this model, also the costs of the system were reduced owing to integrating simultaneous drug pickup and delivery operations. Moreover, regarding the results of simulations, the robust possibilistic model had the best performance among the proposed models. Originality/value This research considers a two-layer vehicle routing in a production-routing problem with inventory planning. Moreover, multisite manufacturing, simultaneous pickup of the expired drugs and delivery of the drugs to the distribution centers are considered. Providing a robust possibilistic model for tackling the uncertainty in demand, costs, production capacity and drug expiration costs is considered as another remarkable feature of the proposed model.

Optimization of the simultaneous pickup and delivery vehicle routing problem based on carbon tax

2019 ◽  
Vol 119 (9) ◽  
pp. 2055-2071 ◽  
Author(s):  
Gaoyuan Qin ◽  
Fengming Tao ◽  
Lixia Li ◽  
Zhenyu Chen
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Carbon Tax ◽  
Pickup And Delivery ◽  
Vehicle Speed ◽  
Low Carbon ◽  
Delivery Vehicle ◽  
Routing Problem ◽  
Content Type ◽  
Simultaneous Pickup And Delivery

Purpose In order to reduce logistics transportation costs and respond to low-carbon economy, the purpose of this paper is to study the more practical and common simultaneous pickup and delivery vehicle routing problem, which considers the carbon tax policy. A low-carbon simultaneous pickup and delivery vehicle routing problem model is constructed with the minimum total costs as the objective function. Design/methodology/approach This study develops a mathematical optimization model with the minimum total costs, including the carbon emissions costs as the objective function. An adaptive genetic hill-climbing algorithm is designed to solve the model. Findings First, the effectiveness of the algorithm is verified by numerical experiments. Second, the research results prove that carbon tax mechanism can effectively reduce carbon emissions within effective carbon tax interval. Finally, the research results also show that, under the carbon tax mechanism, the effect of vehicle speed on total costs will become more obvious with the increase of carbon tax. Research limitations/implications This paper only considers the weight of the cargo, but it does not consider the volume of the cargo. Originality/value Few studies focus on environmental issues in the simultaneous pickup and delivery problem. Thus, this paper constructs a green path optimization model, combining the carbon tax mechanism for the problem. This paper further analyzes the impact of carbon tax value on total costs and carbon emission; at the same time, the effect of vehicle speed on total cost is also analyzed.

Dynamic vehicle routing problem considering simultaneous dual services in the last mile delivery

Kybernetes ◽  
2019 ◽  
Vol 49 (4) ◽  
pp. 1267-1284 ◽  
Author(s):  
Yandong He ◽  
Xu Wang ◽  
Fuli Zhou ◽  
Yun Lin
Keyword(s):  
Vehicle Routing ◽  
Delivery System ◽  
Vehicle Routing Problem ◽  
Mixed Integer ◽  
Dynamic Vehicle Routing ◽  
Dynamic Vehicle Routing Problem ◽  
Routing Problem ◽  
Content Type ◽  
Last Mile ◽  
Last Mile Delivery

Purpose This paper aims to study the vehicle routing problem with dynamic customers considering dual service (including home delivery [HD] and customer pickup [CP]) in the last mile delivery in which three decisions have to be made: determine routes that lie along the HD points and CP facilities; optimize routes in real time, which mode is better between simultaneous dual service (SDS, HD points and CP facilities are served simultaneously by the same vehicle); and respective dual service (RDS, HD points and CP facilities are served by different vehicles)? Design/methodology/approach This paper establishes a mixed integer linear programing model for the dynamic vehicle routing problem considering simultaneous dual services (DVRP-SDS). To increase the practical usefulness and solve large instances, the authors designed a two-phase matheuristic including construction-improvement heuristics to solve the deterministic model and dynamic programing to adjust routes to dynamic customers. Findings The computational experiments show that the CP facilities offer greater flexibility for adjusting routes to dynamic customers and that the SDS delivery system outperforms the RDS delivery system in terms of cost and number of vehicles used. Practical implications The results provide managerial insights for express enterprises from the perspective of operation research to make decisions. Originality/value This paper is among the first papers to study the DVRP-SDS. Moreover, this paper guides the managers to select better delivery mode in the last mile delivery.

Genetic scatter search algorithm to solve the one-commodity pickup and delivery vehicle routing problem

2017 ◽  
Vol 12 (1) ◽  
pp. 2-18 ◽  
Author(s):  
Jalel Euchi
Keyword(s):  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Time Windows ◽  
Scatter Search ◽  
Pickup And Delivery ◽  
Delivery Vehicle ◽  
Routing Problem ◽  
Content Type ◽  
New Variant ◽  
Crossover And Mutation

Purpose In this paper, the author introduces a new variant of the pickup and delivery transportation problem, where one commodity is collected from many pickup locations to be delivered to many delivery locations within pre-specified time windows (one–to many–to many). The author denotes to this new variant as the 1-commodity pickup-and-delivery vehicle routing problem with soft time windows (1-PDVRPTW). Design/methodology/approach The author proposes a hybrid genetic algorithm and a scatter search to solve the 1-PDVRPTW. It proposes a new constructive heuristic to generate the initial population solution and a scatter search (SS) after the crossover and mutation operators as a local search. The hybrid genetic scatter search replaces two steps in SS with crossover and mutation, respectively. Findings So, the author proposes a greedy local search algorithm as a metaheuristic to solve the 1-PDVRPTW. Then, the author proposes to hybridize the metaheuristic to solve this variant and to make a good comparison with solutions presented in the literature. Originality/value The author considers that this is the first application in one commodity. The solution methodology based on scatter search method combines a set of diverse and high-quality candidate solutions by considering the weights and constraints of each solution.

Last-mile distribution planning for fruit-and-vegetable cold chains

2018 ◽  
Vol 29 (3) ◽  
pp. 862-886 ◽  
Author(s):  
Yu-Hsiang Hsiao ◽  
Mu-Chen Chen ◽  
Kuan-Yu Lu ◽  
Cheng-Lin Chin
Keyword(s):  
Vehicle Routing ◽  
Fruits And Vegetables ◽  
Fitness Function ◽  
Time Windows ◽  
Quality Level ◽  
Fruit And Vegetable ◽  
Routing Problem ◽  
Content Type ◽  
Fleet Size ◽  
Last Mile

Purpose The purpose of this paper is to formulate and solve a last-mile distribution plan problem with concern for the quality of fruits and vegetables in cold chains. Design/methodology/approach The vehicle routing problem with time windows (VRPTW) is extended based on the characteristics of fruit-and-vegetable cold chains. The properties of multiple perishable foods, continuing decline in quality, various requirements for quality levels and optimal temperature settings during vehicle transportation are considered in the VRPTW. The product quality level is defined by the estimation of residual shelf life, which changes with temperature, and is characterized by a stepped decrease during the transportation process as time goes on. A genetic algorithm (GA) is adapted to solve the problem because of its convincing ability to solve VRPTW-related problems. For this purpose, solution encoding, a fitness function and evolution operators are designed to deal with the complicated problem herein. Findings A distribution plan including required fleet size, vehicle routing sequence and what quality level should be shipped out to account for the quality degradation during vehicle transportation is generated. The results indicate that the fulfillment of various requirements of different customers for various fruits and vegetables and quality levels can be ensured with cost considerations. Originality/value This study presents a problem for last-mile delivery of fresh fruits and vegetables which considers multiple practical scenarios not studied previously. A solution algorithm based on a GA is developed to address this problem. The proposed model is easily applied to other types of perishable products.

Scheduling the in-house logistics distribution for automotive assembly lines with just-in-time principles

2017 ◽  
Vol 37 (1) ◽  
pp. 51-63 ◽  
Author(s):  
Binghai Zhou ◽  
Tao Peng
Keyword(s):  
Real World ◽  
Approximate Solutions ◽  
Distribution Model ◽  
Small Scale ◽  
Just In Time ◽  
Similar Distribution ◽  
Assembly Lines ◽  
Content Type ◽  
Bee Colony ◽  
Automotive Assembly

Purpose This paper aims to investigate the just-in-time (JIT) in-house logistics problem for automotive assembly lines. A point-to-point (P2P) JIT distribution model has been formulated to specify the destination station and parts quantity of each delivery for minimizing line-side inventory levels. Design/methodology/approach An exact backtracking procedure integrating with dominance properties is presented to cope with small-scale instances. As for real-world instances, this study develops a modified discrete artificial bee colony (MDABC) metaheuristic. The neighbor search of MDABC is redefined by a novel differential evolution loop and a breadth-first search. Findings The backtracking method has efficaciously cut unpromising branches and solved small-scale instances to optimality. Meanwhile, the modifications have enhanced exploitation abilities of the original metaheuristic, and good approximate solutions are obtained for real-world instances. Furthermore, inventory peaks are avoided according to the simulation results which validates the effectiveness of this mathematical model to facilitate an efficient JIT parts supply. Research limitations/implications This study is applicable only if the breakdown of transport devices is not considered. The current work has effectively facilitated the P2P JIT logistics scheduling in automotive assembly lines, and it could be modified to tackle similar distribution problems featuring time-varying demands. Originality/value Both limited vehicle capacities and no stock-outs constraints are considered, and the combined routing and loading problem is solved satisfactorily for an efficient JIT supply of material in automotive assembly lines.

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