An improved particle swarm optimization for carton heterogeneous vehicle routing problem with a collection depot

Yao, Baozhen; Yu, Bin; Hu, Ping; Gao, Junjie; Zhang, Mingheng

doi:10.1007/s10479-015-1792-x

Cited by 133 publications

(76 citation statements)

References 34 publications

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“…Cordeau [23] presented recent optimization models for the most commonly studied rail transportation problems, which concentrated on routing and scheduling problems. Similar research problems have been studied by Chakroborty [24], Yao et al [25,26], and Yu et al [27].…”

Section: Introductionmentioning

confidence: 55%

Optimization of the Waterbus Operation Plan Considering Carbon Emissions: The Case of Zhoushan City

Guan

et al. 2015

Sustainability

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Abstract:Recently, as more people are concerned with the issues around environment protection, research about how to reduce carbon emissions has drawn increasing attention. Encouraging public transportation is an effective measure to reduce carbon emissions. However, overland public transportation does less to lower carbon because of the gradually increasing pressure of the urban road traffic. Therefore, the waterbus along the coast becomes a new direction of the urban public transport development. In order to optimize the operation plan of the waterbus, a bi-level model considering carbon emissions is proposed in this paper. In the upper-level model, a multiple objective model is established, which considers both the interests of the passengers and the operator while considering the carbon emissions. The lower-level model is a traffic model split by using a Nested Logit model. A NSGA-II (Non-dominated Sorting Genetic Algorithm-II) algorithm is proposed to solve the model. Finally, the city of Zhoushan is chosen as an example to prove the feasibility of the model and the algorithm. The result shows that the proposed model for waterbus operation optimization can efficiently reduce transportation carbon emissions and satisfy passenger demand at the same time.

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Section: Introductionmentioning

confidence: 55%

Optimization of the Waterbus Operation Plan Considering Carbon Emissions: The Case of Zhoushan City

Guan

et al. 2015

Sustainability

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“…[19][20][21][22] As for the ship route planning and scheduling problem, many pure or MILP models and their extensions are developed, which can refer to these literatures. [23][24][25][26][27][28][29][30][31] Zeng and Yang 32 combined integer programming with heuristics. Cho and Perakis, 33 considering the fleet size, mixing, and delivery route assignment, presented integer linear programming models over a long-term planning horizon.…”

Section: Literature Reviewmentioning

confidence: 99%

Fleet routing and scheduling problem based on constraints of chance

Guan

Peng

Chen

et al. 2017

Advances in Mechanical Engineering

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Tramp shipping transport is an important part of ocean transportation. However, facing the spot market with many uncertain conditions, it is not easy for fleet operators to plan vessel's routes and schedule in the later period time, especially considering the situation that loading time window for a lot of cargoes has strong randomness. This article designed a linear programming model with chance constraints for the time window of loading cargo. Before the optimization, a survey for the waiting time of ships for berths is carried out in some of the ports with large export volume. Combined with the degree of acceptance how long ship owners can wait for the berth, the uncertain time window constraints can be transformed into deterministic constraints. The model is solved by column generation optimization technique. The model and algorithm are verified by a case of Panamax bulker fleet planning in real market. The results show that the model and the algorithm proposed in the article can well work on large-scale problem and can achieve good precision. Also, via sensitivity analysis, we provide decision makers good reference to balance profit and risks coming from randomness.

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“…However, in practical terms, the number of passengers served by a cruise line is closely related to its itineraries [27][28][29]. Many customers specifically consider the unique ports of call offered when selecting a cruise package [30][31]. Thus, it is not possible to obtain a practical result merely by minimizing voyage costs.…”

Section: Itinerary Optimization Modelmentioning

confidence: 99%