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Open research questions in Vehicle Routing Optimization Methods

52 unresolved questions extracted from the limitations and future-work sections of 557 Vehicle Routing Optimization Methods papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • Further research can be done to test the algorithm on large-scale cases and real-world applications. The method can be extended to other logistics systems with similar constraints and objectives.

    Research on Cold Chain Logistics Route Optimization Based on Improved Genetic Algorithm · 2026 · DOI

  • The optimization of cold chain logistics distribution is a complex problem due to temperature control requirements and multiple operational constraints. Existing research mainly focuses on cost control, carbon emission constraints, and distribution efficiency, but may not fully address the complexities of cold chain logistics.

    Research on Cold Chain Logistics Route Optimization Based on Improved Genetic Algorithm · 2026 · DOI

  • The Capacitated Arc Routing Problem does not account for priority edges. Prior algorithms for CARP do not consider priority edges.

    Applying priority edges for Capacitated Arc Routing Problem: problem extension and genetic algorithm · 2026 · DOI

  • The need to consider multiple objectives in the location routing problem. The impact of traffic congestion on fuel consumption and GHG emissions. The importance of patient satisfaction in the location routing problem.

    Optimizing sustainable healthcare location routing problem: Incorporating triage, automated medicine lockers, and soft time windows · 2026 · DOI

  • The proposed method is limited to the Travelling Salesman Problem. The evaluation is based on a single adapted model using a single sample for adaptation.

    Combinatorial Route Optimization Using Near-Training-Free Foundation Models · 2026 · DOI

  • Future research can explore the application of the proposed method to other Combinatorial Optimization problems. Further studies can investigate the use of other foundation models for Combinatorial Route Optimization problems.

    Combinatorial Route Optimization Using Near-Training-Free Foundation Models · 2026 · DOI

  • The existing drug distribution channel planning is challenged by fluctuations in demand and policy fluctuations. The existing drug distribution channel planning is heavily reliant on manual work experience and static scheduling models.

    Optimizing the Dual-Channel Drug Distribution Path of Medical Insurance Using Graph Attention Network · 2026 · DOI

  • Traditional algorithms may not be effective in solving logistics distribution route optimization problems.

    Modeling for Logistics Distribution Route Optimization · 2026 · DOI

  • Rapidly changing environments. Limited resources. Damaged infrastructure. Increased security risks.

    Methods of deep reinforcement learning for adaptive optimization of military logistics routes · 2026 · DOI

  • Demand uncertainty. Computational complexity. Limited market scale and penetration rate of pallet pooling.

    The location-routing problem in the pallet pooling system with demand uncertainty · 2026 · DOI

  • The number of vehicles is not part of the optimisation, - The solution time (T) is a challenge, - The percentage gap (G%) is a challenge

    Results and Comparison of Results for the Pollution Routing Problem · 2026 · DOI

  • The Wilcoxon signed-rank test mentioned as validation is not detailed in the excerpt. Formal statistical significance testing results and effect sizes comparing AAACO to each competing algorithm across the 10 benchmark instances would strengthen claims about robustness and superiority.

    A hybrid artificial algae and ant colony optimization algorithm for combinatorial problems · 2026 · DOI

  • The paper evaluates AAACO exclusively on symmetric Euclidean TSP benchmarks (berlin52, a280, ch150, eil101, gil262, d493, kroA100, pr76, bays29, u1060). Application to asymmetric TSP variants, vehicle routing problems with time windows, or other permutation-based combinatorial optimization problems remains unexplored.

    A hybrid artificial algae and ant colony optimization algorithm for combinatorial problems · 2026 · DOI

  • Future research can focus on extending the proposed method to other micro-mobility services. Future research can focus on comparing the proposed method with other optimization methods. Future research can focus on evaluating the proposed method in real-world scenarios.

    Micro-mobility dispatch optimization via quantum annealing incorporating historical data · 2026 · DOI

  • The paper identifies a research gap in the lack of efficient and adaptive dispatch algorithms for micro-mobility services. The paper identifies a research gap in the lack of incorporation of historical usage data in dispatch formulations.

    Micro-mobility dispatch optimization via quantum annealing incorporating historical data · 2026 · DOI

  • Future research should focus on integrating thermodynamic variability, deterioration dynamics, and energy consumption modeling in RVRP models. Further studies can build on the co-citation network analysis to explore the evolution of the RVRP literature.

    Mapping the intellectual structure of the refrigerated vehicle routing problem: research perspectives and structural knowledge gaps · 2026 · DOI

  • The study identifies a gap in the integration of thermodynamic variability, deterioration dynamics, and energy consumption modeling in RVRP models. The field's intellectual structure remains fragmented across methodological traditions, limiting cross-perspective integration.

    Mapping the intellectual structure of the refrigerated vehicle routing problem: research perspectives and structural knowledge gaps · 2026 · DOI

  • The lack of consideration of multiple objectives in the location routing problem. The need for a fundamental rethinking of distribution network design in the post-pandemic era.

    Optimizing sustainable healthcare location routing problem: Incorporating triage, automated medicine lockers, and soft time windows · 2026 · DOI

  • The study suggests further research on the application of the proposed framework. The study recommends evaluating the framework with different datasets and scenarios.

    An Integrated Circular Intuitionistic Fuzzy MCDM Framework with Radius Operators for Same-Day Delivery Service Selection · 2026 · DOI

  • The study identifies a gap in the existing decision-making frameworks for SDD service selection. The study addresses the uncertainty and ambiguity in the evaluation of alternatives.

    An Integrated Circular Intuitionistic Fuzzy MCDM Framework with Radius Operators for Same-Day Delivery Service Selection · 2026 · DOI

  • Evaluation of Q-learning variants for other optimization problems. Comparison of Q-learning with other optimization methods. Application of the study's findings to real-world instances.

    Reinforcement learning for solving optimization problems: Opportunities and limitations on the example of the assignment problem · 2026 · DOI

  • The sample size is limited (5 independent runs for each configuration) - The study may not fully capture the dispersion inherent in the stochastic genetic algorithm

    Use of greedy and genetic algorithms for optimal mobile network base station placement · 2026 · DOI

  • Using a significantly larger number of iterations (e.g., 30 or more) for genetic algorithm evaluation - Conducting an extended statistical analysis for confirmation of the absolute stability of the method

    Use of greedy and genetic algorithms for optimal mobile network base station placement · 2026 · DOI

  • The lack of adaptability to changing situations in real-time is a gap in current methods. Traditional static routing methods are ineffective in dynamic and uncertain operational conditions.

    Methods of deep reinforcement learning for adaptive optimization of military logistics routes · 2026 · DOI

  • To further analyze the impact of demand uncertainty on the pallet pooling system. To develop more efficient algorithms to solve the combinatorial optimization problem. To apply the proposed model and algorithm to other logistics systems.

    The location-routing problem in the pallet pooling system with demand uncertainty · 2026 · DOI

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52 open questions have been extracted from the limitations and future-work passages of 557 Vehicle Routing Optimization Methods papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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