Solving the vehicle routing problem with time windows and multiple routes exactly using a pseudo-polynomial model

Macedo, Rita; Alves, Cláudio; Carvalho, José Valério de; Clautiaux, François; Hanafi, Saïd

doi:10.1016/j.ejor.2011.04.037

Cited by 90 publications

(60 citation statements)

References 20 publications

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“…If the delivery vehicle postpones arriving at the customer's location, it will get late penalty P2. The penalty cost equals 2 …”

Section: The Mathematical Model Of Associated Scheduling Transportatimentioning

confidence: 99%

See 1 more Smart Citation

Study on Improved Chaotic Particle Swarm Optimization Based Logistics and Transport Scheduling Problems with Soft Time Windows

Chen¹,

Guo²

2015

IJGDC

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Research the Incident Vehicle Routing Problem with Soft Time-windows (IVRP-STW).Associated logistics scheduling problem with soft time windows using the logistic function optimization method to improve the chaotic particle algorithm, compared with the GA and the standard PSO algorithm. Simulation results show that such optimization method can effectively improve the global search of the particles in the particle swarm and the ability of local search is effective in resolving such problems.

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“…If the delivery vehicle postpones arriving at the customer's location, it will get late penalty P2. The penalty cost equals 2 …”

Section: The Mathematical Model Of Associated Scheduling Transportatimentioning

confidence: 99%

“…Rita Macedo etc. [2] solve VRP through the establishment of pseudo-polynomial model for multi-path with time windows. Yannis Marinakis etc[3] studied hybrid genetic particle swarm optimization algorithm based VRP.…”

Section: Introductionmentioning

confidence: 99%

Study on Improved Chaotic Particle Swarm Optimization Based Logistics and Transport Scheduling Problems with Soft Time Windows

Chen¹,

Guo²

2015

IJGDC

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“…Ordering of nodes within clusters and scheduling of vehicle arrival times at the nodes is performed in the third phase. In [22], feasible routes are generated first, then a reduction algorithm based on dominance rules is applied to reduce the number of feasible routes and finally the routes for each ship are selected based on solving an exact optimization problem. The tabu search technique, introduced by Glover [16], has been highly successful when applied to the VRP, see [11].…”

Section: Literature Reviewmentioning

confidence: 99%

Downstream logistics optimization at EWOS Norway

Branda¹,

Haugen²,

Haugen³

et al. 2017

Math. Appl.

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Abstract. The Norwegian company EWOS AS produces fish feed for the salmon farming industry, supplying approximately 300 customers spread along the coast of Norway. The feed is produced at three factory locations and distributed by a fleet of 10 dedicated vessels. The high seasonality of the demand and the large number of customers make the distribution planning a substantial challenge. EWOS handles it by operating a system of mostly fixed routes with decentralized planning at each factory. The distribution can be described as a multi-depot vehicle routing problem with time windows, multiple vehicle usage, inter-depot routes, heterogeneous fleet and a rolling horizon. The paper presents a mathematical model for this problem, which is solved by heuristics and meta heuristics. Based on detailed historical data collected by EWOS during the autumn of 2010, the model has proposed a dynamic set of routes with a significant reduction of travelled distance -close to 30% -and an increase of average vessel fill-rate -from 60% up to 95%. This implies a substantial fuel saving, with a positive environmental impact, and also a potential for downscaling the fleet, with additional considerable cost savings for the company.

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“…Rita Macedo [2] solute the VRP using pseudo-polynomial. Yannis Marinakis [3] studied the hybrid genetic PSO VRP. In domestic, Cheng Jin, Cai Yanguang, Li Yongsheng studied the union scheduling problem.…”

Section: Introductionmentioning

confidence: 99%

Research on Route guidance of logistic scheduling problem under fuzzy time window

Chen¹,

Guo²

2014

Advanced Science and Technology Letters

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Abstract.Study the problem of logistic scheduling problem with fuzzy time window, construct mathematical model, propose double objective function method. In the solution process, for the feature of the double objective functions, use the phased . In the first phase, use the chaos PSO to get the optimal solution. In the second phase, use simulated annealing algorithm and the preliminary solutions got from the first phase to solute the objective function.

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Solving the vehicle routing problem with time windows and multiple routes exactly using a pseudo-polynomial model

Cited by 90 publications

References 20 publications

Study on Improved Chaotic Particle Swarm Optimization Based Logistics and Transport Scheduling Problems with Soft Time Windows

Study on Improved Chaotic Particle Swarm Optimization Based Logistics and Transport Scheduling Problems with Soft Time Windows

Downstream logistics optimization at EWOS Norway

Research on Route guidance of logistic scheduling problem under fuzzy time window

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