The aquaculture service vessel routing problem with time dependent travel times and synchronization constraints

2021 ◽  
pp. 105316
Author(s):  
Ingeborg Margrete Lianes ◽  
Maren Theisen Noreng ◽  
Kjetil Fagerholt ◽  
Hans Tobias Slette ◽  
Frank Meisel
Keyword(s):  
Time Dependent ◽  
Travel Times ◽  
Routing Problem ◽  
Synchronization Constraints

scholarly journals Urban Freight Management with Stochastic Time-Dependent Travel Times and Application to Large-Scale Transportation Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Shichao Sun ◽  
Zhengyu Duan ◽  
Dongyuan Yang
Keyword(s):  
Large Scale ◽  
Time Window ◽  
Transportation Networks ◽  
Optimal Path ◽  
Time Dependent ◽  
Travel Times ◽  
Urban Network ◽  
Routing Problem ◽  
On The Road ◽  
Stochastic Time

This paper addressed the vehicle routing problem (VRP) in large-scale urban transportation networks with stochastic time-dependent (STD) travel times. The subproblem which is how to find the optimal path connecting any pair of customer nodes in a STD network was solved through a robust approach without requiring the probability distributions of link travel times. Based on that, the proposed STD-VRP model can be converted into solving a normal time-dependent VRP (TD-VRP), and algorithms for such TD-VRPs can also be introduced to obtain the solution. Numerical experiments were conducted to address STD-VRPTW of practical sizes on a real world urban network, demonstrated here on the road network of Shenzhen, China. The stochastic time-dependent link travel times of the network were calibrated by historical floating car data. A route construction algorithm was applied to solve the STD problem in 4 delivery scenarios efficiently. The computational results showed that the proposed STD-VRPTW model can improve the level of customer service by satisfying the time-window constraint under any circumstances. The improvement can be very significant especially for large-scale network delivery tasks with no more increase in cost and environmental impacts.

Exact Branch-Price-and-Cut for a Hospital Therapist Scheduling Problem with Flexible Service Locations and Time-Dependent Location Capacity

2021 ◽  
Author(s):  
Alexander Jungwirth ◽  
Guy Desaulniers ◽  
Markus Frey ◽  
Rainer Kolisch
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Cutting Planes ◽  
Time Windows ◽  
Time Dependent ◽  
Planning Problem ◽  
Routing Problem ◽  
Number Of Patients ◽  
New Variant ◽  
Synchronization Constraints

We study a new variant of the vehicle routing problem, which arises in hospital-wide scheduling of physical therapists. Multiple service locations exist for patients, and resource synchronization for the location capacities is required as only a limited number of patients can be treated at one location at a time. Additionally, operations synchronization between treatments is required as precedence relations exist. We develop an innovative exact branch-price-and-cut algorithm including two approaches targeting the synchronization constraints (1) based on branching on time windows and (2) based on adding combinatorial Benders cuts. We optimally solve realistic hospital instances with up to 120 treatments and find that branching on time windows performs better than adding cutting planes. Summary of Contribution: We present an exact branch-price-and-cut (BPC) algorithm for the therapist scheduling and routing problem (ThSRP), a daily planning problem arising at almost every hospital. The difficulty of this problem stems from its inherent structure that features routing and scheduling while considering multiple possible service locations with time-dependent location capacities. We model the ThSRP as a vehicle routing problem with time windows and flexible delivery locations and synchronization constraints, which are properties relevant to other vehicle routing problem variants as well. In our computational study, we show that the proposed exact BPC algorithm is capable of solving realistic hospital instances and can, thus, be used by hospital planners to derive better schedules with less manual work. Moreover, we show that time window branching can be a valid alternative to cutting planes when addressing synchronization constraints in a BPC algorithm.

Routing Electric Vehicles on Congested Street Networks

2020 ◽  
Author(s):  
Alexandre M. Florio ◽  
Nabil Absi ◽  
Dominique Feillet
Keyword(s):  
Electric Vehicles ◽  
Traffic Congestion ◽  
Control Policy ◽  
Time Dependent ◽  
Travel Times ◽  
Routing Problem ◽  
Promising Alternative ◽  
Street Networks ◽  
Time Control ◽  
The Impact

Freight distribution with electric vehicles (EVs) is a promising alternative to reduce the carbon footprint associated with city logistics. Algorithms for planning routes for EVs should take into account their relatively short driving range and the effects of traffic congestion on the battery consumption. This paper proposes new methodology and illustrates how it can be applied to solve an electric vehicle routing problem with stochastic and time-dependent travel times where battery recharging along routes is not allowed. First, a new method for generating network-consistent (correlated in time and space) and time-dependent speed scenarios is introduced. Second, a new technique for applying branch and price on instances defined on real street networks is developed. Computational experiments demonstrate the effectiveness of the approach for finding optimal or near-optimal solutions in instances with up to 133 customers and almost 1,500 road links. With a high probability, the routes in the obtained solutions can be performed by EVs without requiring intermediate recharging stops. An execution time control policy to further reduce the chances of stranded EVs is also presented. In addition, we measure the cost of independence, which is the impact on solution feasibility when travel times are assumed statistically independent. Last, we give directions on how to extend the proposed framework to handle recourse actions.

scholarly journals A model for the time dependent vehicle routing problem with time windows under traffic conditions with intelligent travel times

2021 ◽  
Author(s):  
Saeed Khanchehzarrin ◽  
Maral Shahmizad ◽  
Iraj Mahdavi ◽  
Nezam Mahdavi-Amiri ◽  
Peiman Ghasemi
Keyword(s):  
Travel Time ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Programming Model ◽  
Time Windows ◽  
Time Dependent ◽  
Mixed Integer ◽  
Travel Times ◽  
Routing Problem ◽  
Traffic Conditions

A new mixed-integer nonlinear programming model is presented for the time-dependent vehicle routing problem with time windows and intelligent travel times. The aim is to minimize fixed and variable costs, with the assumption that the travel time between any two nodes depends on traffic conditions and is considered to be a function of vehicle departure time. Depending on working hours, the route between any two nodes has a unique traffic parameter. We consider each working day to be divided into several equal and large intervals, termed as a scenario. Here, allowing for long distances between some of the nodes, travel time may take more than one scenario, resulting in resetting the scenario at the start of each large interval. This repetition of scenarios has been used in modeling and calculating travel time. A tabu search optimization algorithm is devised for solving large problems. Also, after linearization, a number of random instances are generated and solved by the CPLEX solver of GAMS to assess the effectiveness of our proposed algorithm. Results indicate that the initial travel time is estimated appropriately and updated properly in accordance with to the repeating traffic conditions.

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