A scenario decomposition algorithm for strategic time window assignment vehicle routing problems

Subramanyam, Anirudh; Wang, Akang; Gounaris, Chrysanthos E.

doi:10.1016/j.trb.2018.09.008

Cited by 30 publications

(7 citation statements)

References 37 publications

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“…The vehicle routing problem with soft time windows (where a penalty is imposed on vehicles for early or late arrivals at customer nodes) [29]- [34] and strict time windows (when vehicles cannot satisfy customer demand outside a defined arrival time window) [35]- [38] have also been addressed in the state-of-the-art. Bae and Moon [36] focused on the vehicle routing problem with strict time windows, where several depots were considered.…”

Section: B the Vehicle Routing Problemmentioning

confidence: 99%

“…Furthermore, when compared with some other solution algorithms in the state-of-the-art, the TS algorithm performed better in terms of the solution quality. Subramanyam et al [38] considered operational uncertainties in the vehicle routing problem with strict time windows. A two-stage stochastic optimization model was formulated.…”

Section: B the Vehicle Routing Problemmentioning

confidence: 99%

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An Optimization Model and Solution Algorithms for the Vehicle Routing Problem With a “Factory-in-a-Box”

Pasha

Dulebenets

Kavoosi³

et al. 2020

IEEE Access

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The "factory-in-a-box" concept involves assembling production modules (i.e., factories) in containers and transporting the containers to different customer locations. Such a concept could be highly effective during emergencies, when there is an urgent demand for products (e.g., the COVID-19 pandemic). The "factory-in-a-box" planning problem can be divided into two sub-problems. The first sub-problem deals with the assignment of raw materials to suppliers, sub-assembly decomposition, assignment of subassembly modules to manufacturers, and assignment of tasks to manufacturers. The second sub-problem focuses on the transport of sub-assembly modules between suppliers and manufacturers by assigning vehicles to locations, deciding the order of visits for suppliers, manufacturers, and customers, and selecting the appropriate routes within the transportation network. This study addresses the second sub-problem, which resembles the vehicle routing problem, by developing an optimization model and solution algorithms in order to optimize the "factory-in-a-box" supply chain. A mixed-integer linear programming model, which aims to minimize the total cost of the "factory-in-a-box" supply chain, is presented in this study. CPLEX is used to solve the model to the global optimality, while four metaheuristic algorithms, including the Evolutionary Algorithm, Variable Neighborhood Search, Tabu Search, and Simulated Annealing, are employed to solve the model for large-scale problem instances. A set of numerical experiments, conducted for a case study of "factory-in-a-box", demonstrate that the Evolutionary Algorithm outperforms the other metaheuristic algorithms developed for the model. Some managerial insights are outlined in the numerical experiments as well. INDEX TERMS Factory-in-a-box, metaheuristics, supply chains, urgent demand, vehicle routing problem.

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Section: B the Vehicle Routing Problemmentioning

confidence: 99%

Section: B the Vehicle Routing Problemmentioning

confidence: 99%

An Optimization Model and Solution Algorithms for the Vehicle Routing Problem With a “Factory-in-a-Box”

Pasha

Dulebenets

Kavoosi³

et al. 2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…In TWAVRP, candidate time windows are assigned to customers to improve the operational efficiency of logistics networks [53,54]. Subramanyam et al [55] introduced a scenario decomposition algorithm to solve TWAVRP for minimizing the expected routing cost of logistics facility. Neves-Moreira et al [56] presented a twostage stochastic optimization problem of TWAVRP and addressed it by using a fix-and-optimize-based metaheuristic.…”

Section: Literature Reviewmentioning

confidence: 99%

Multidepot Recycling Vehicle Routing Problem with Resource Sharing and Time Window Assignment

Wang

Guan

et al. 2021

Journal of Advanced Transportation

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This study aims to provide tactical and operational decisions in multidepot recycling logistics networks with consideration of resource sharing (RS) and time window assignment (TWA) strategies. The RS strategy contributes to efficient resource allocation and utilization among recycling centers (RCs). The TWA strategy involves assigning time windows to customers to enhance the operational efficiency of logistics networks. A biobjective mathematical model is established to minimize the total operating cost and number of vehicles for solving the multidepot recycling vehicle routing problem with RS and TWA (MRVRPRSTWA). A hybrid heuristic algorithm including 3D k-means clustering algorithm and nondominated sorting genetic algorithm- (NSGA-) II (NSGA-II) is designed. The 3D k-means clustering algorithm groups customers into clusters on the basis of their spatial and temporal distances to reduce the computational complexity in optimizing the multidepot logistics networks. In comparison with NSGA algorithm, the NSGA-II algorithm incorporates an elitist strategy, which can improve the computational speed and robustness. In this study, the performance of the NSGA-II algorithm is compared with the other two algorithms. Results show that the proposed algorithm is superior in solving MRVRPRSTWA. The proposed model and algorithm are applied to an empirical case study in Chongqing City, China, to test their applicability in real logistics operations. Four different scenarios regarding whether the RS and TWA strategies are included or not are developed to test the efficacy of the proposed methods. The results indicate that the RS and TWA strategies can optimize the recycling services and resource allocation and utilization and enhance the operational efficiency, thus promoting the sustainable development of the logistics industry.

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“…Zhou et al [25] proposed the compensation mechanism of delayed distribution based on interest balance. Some researchers pay more attention to the logistics distribution problem [26][27][28][29][30][31][32][33][34][35][36][37].…”

Section: Introductionmentioning

confidence: 99%

Research on the n-Stage Delay Distribution Method Based on a Compensation Mechanism in a Random Environment

Zhou

2022

Axioms

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With the development of logistics, the delayed distribution problem based on a compensation mechanism has appeared. The core of this problem is to decide whether to delay the distribution at the beginning of each stage and how to compensate the customers if delay occurs. In this paper, beginning with the 2 and 3-stage delay distribution problem, the characteristics and computational complexity of the model are analyzed, and a formal model description of the n-stage problem is given. The expected value and variance are used as the centralized quantization description strategy for random variables, and the expected value model and the generalized expectation value model for solving the delay distribution problem are given. The solution algorithm is given, and the dependence of the single transport cost of each transport vehicle and the penalty for each car delay in a period-of-time distribution are analyzed. Combined with specific examples, theoretical analysis and example calculations show that the formal description model is a good platform for further combinations of solution methods. This method extends the general delayed distribution problem to multi-stage delayed distribution, which has guiding significance for decision-makers. The proposed model has solid system structure features and interpretability, and could be used in a wide variety of applications.

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A scenario decomposition algorithm for strategic time window assignment vehicle routing problems

Cited by 30 publications

References 37 publications

An Optimization Model and Solution Algorithms for the Vehicle Routing Problem With a “Factory-in-a-Box”

An Optimization Model and Solution Algorithms for the Vehicle Routing Problem With a “Factory-in-a-Box”

Multidepot Recycling Vehicle Routing Problem with Resource Sharing and Time Window Assignment

Research on the n-Stage Delay Distribution Method Based on a Compensation Mechanism in a Random Environment

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