The time-dependent vehicle routing problem with soft time windows and stochastic travel times

This paper presents a saving-based heuristic for the vehicle routing problem with time windows and stochastic travel times (VRPTWSTT). One of the basic ideas of the heuristic is to advance the latest service start time of each customer by a certain period of time. In this way, the reserved time can be used to cope with unexpected travel time delay when necessary. Another important idea is to transform the VRPTWSTT to a set of vehicle routing problems with time windows (VRPTW), each of which is defined by a given percentage used to calculate the reserved time for customers. Based on the above two key ideas, a three-stage heuristic that includes the “problem transformation” stage, the “solution construction” stage, and the “solution improvement” stage is developed. After the problem transformation in the first stage, the work of the next two stages is to first construct an initial solution for each transformed VRPTW by improving the idea of the classical Clarke-Wright heuristic and then further improve the solution. Finally, a number of numerical experiments are conducted to evaluate the efficiency of the described methodology under different uncertainty levels.

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Multi-Trip Time-Dependent Vehicle Routing Problem with Soft Time Windows and Overtime Constraints

Networks and Spatial Economics ◽

10.1007/s11067-019-09492-3 ◽

2020 ◽

Vol 20 (2) ◽

pp. 549-598

Author(s):

Ampol Karoonsoontawong ◽

Puntipa Punyim ◽

Wanvara Nueangnitnaraporn ◽

Vatanavongs Ratanavaraha

Keyword(s):

Vehicle Routing ◽

Vehicle Routing Problem ◽

Time Windows ◽

Time Dependent ◽

Routing Problem ◽

Soft Time Windows ◽

Trip Time

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

RAIRO - Operations Research ◽

10.1051/ro/2021098 ◽

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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