SMT-LH: A New Satisfiability Modulo Theory-Based Technique for Solving Vehicle Routing Problem with Time Window Constraints

Rizkallah, Lydia W.; Ahmed, Mona F.; Darwish, Nevin M.

doi:10.1093/comjnl/bxy127

Cited by 4 publications

(3 citation statements)

References 28 publications

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“…where ( 7) is the objective function, which indicates the minimization of the total energy consumption of distribution transport. Equation (8) indicates that the probability of a vehicle's actual load being greater than its maximum planned load should be less than the predetermined target risk probability. Equations ( 9)- (11) ensure that each vehicle departs from the center of distribution, serves the customer, and then leaves and eventually returns to the distribution center.…”

Section: Lvgvrpsd Modelmentioning

confidence: 99%

“…In [7], a vehicle routing problem to be solved through heuristic procedures was proposed. In [8], the satisfiability model theory was successfully used to solve the vehicle routing problem with time window constraints. e quality of the solution proved to be competitive compared to other optimization techniques because the solution time significantly reduced and opened the door to larger problems.…”

Section: Introductionmentioning

confidence: 99%

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Multipoint Distribution Vehicle Routing Optimization Problem considering Random Demand and Changing Load

Pan

Yong

Gao

2022

Security and Communication Networks

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In the distribution scenario, the using cost of vehicles is closely related to energy consumption, and the energy consumption rate of a vehicle is closely related to the size of its load. The traditional vehicle routing optimization model takes the shortest distance as the optimization goal when the customer demand is determined, while the influence of the random demand and the changing load on the energy consumption and cost of vehicles in the process of distribution is ignored. Therefore, in this paper, load varying vehicle routing problem with stochastic demands (LVGVRPSD) model is proposed with the goal of minimizing transportation energy consumption and considering the load variability and the randomness of customer demand. K-means clustering algorithm is combined with ant colony optimization (ACO) to solve the problem, and the constraint of risk probability is introduced to describe the vehicle overload problem. Examples in the standard vehicle routing problem test data set are provided and analyzed. LVGVRPSD is also compared with the traditional capacitated vehicle routing problem (CVRP) model. The case study results show that the vehicle energy consumption can be reduced by 2% in the model that considers changing load compared to the model that does not consider changing load. The results illustrate that the method of path optimization is more advantageous and reasonable in the pursuit of reducing energy consumption, when the changing load and the random demand of customer are considered.

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Section: Lvgvrpsd Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multipoint Distribution Vehicle Routing Optimization Problem considering Random Demand and Changing Load

Pan

Yong

Gao

2022

Security and Communication Networks

View full text Add to dashboard Cite

show abstract

“…The squirrel search algorithm assumes that there are squirrels on trees in the forest, and there is only one squirrel in each tree, and each squirrel forages for food and maximizes the available food resources through dynamic actions (see e.g. [14]). There are only three kinds of trees in the forest: Common tree, oak tree and walnut tree, of which oak tree and walnut tree are the food sources of squirrels, and only three oak trees and one walnut tree are set to exist in the forest area.…”

Section: Squirrel Search Algorithm Solution Designmentioning

confidence: 99%

Location and Layout of Common Storage and Multichannel Common Distribution considering Time Windows

Bi-qin

Yang²,

Jiang

et al. 2021

Wireless Communications and Mobile Computing

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In the process of logistic activities of common storage and common distribution, due to problems such as urban traffic congestion period, parking restriction, working time restriction, and road restriction time, people often agree on the arrival time for customer orders, so that the receiving and delivering parties can connect in time and speed up unloading and distribution. Therefore, considering the actual distribution operation, it is necessary to consider the location and layout of common storage and multichannel common distribution in time windows. This paper takes multichannel common storage and common distribution as the research object, combines with the actual distribution situation, considers the location and distribution route optimization of the common storage and common distribution mode under the condition of time windows, takes the form of linking time windows with distribution time completion efficiency, and forms a reverse constraint on the objective function by time completion efficiency, thus realizing the double-objective optimization of “minimizing the total cost and satisfying the time windows.” In addition, through the comparison of various intelligent algorithms, find that the squirrel search algorithm (SSA) has more stable performance and better solution results.

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A Compositional Algorithm for the Conflict-Free Electric Vehicle Routing Problem

Roselli

Götvall

Fabian

et al. 2022

IEEE Trans. Automat. Sci. Eng.

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SMT-LH: A New Satisfiability Modulo Theory-Based Technique for Solving Vehicle Routing Problem with Time Window Constraints

Cited by 4 publications

References 28 publications

Multipoint Distribution Vehicle Routing Optimization Problem considering Random Demand and Changing Load

Multipoint Distribution Vehicle Routing Optimization Problem considering Random Demand and Changing Load

Location and Layout of Common Storage and Multichannel Common Distribution considering Time Windows

A Compositional Algorithm for the Conflict-Free Electric Vehicle Routing Problem

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