Intelligent Multi-Start Methods

Martı́, Rafael; Aceves, Ricardo; León, Teresa; Moreno-Vega, J. Marcos; Duarte, Abraham

doi:10.1007/978-3-319-91086-4_7

Cited by 6 publications

(2 citation statements)

References 50 publications

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“…Here, we draw on some of their ideas and then present a hybrid metaheuristic approach to improve the construction heuristic solutions. One way to achieve diversification is to re-start the procedure from a new solution (Martí et al 2019). It is clear that if the iteration number is fixed, the initial solution has a significant impact on quality of the final solution.…”

Section: Algorithm 1 Construction Heuristicmentioning

confidence: 99%

Two-echelon urban deliveries using autonomous vehicles

Puchinger

Sun

2020

Transportation Research Part E: Logistics and Transportation Re

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We introduce a two-echelon urban delivery problem with second-level unmanned vehicles. This problem typically applies for delivering parcels or other small commodities to pedestrianized areas such as campuses or residential clusters. To model the proposed vehicle routing problem, we introduce a mixed-integer program. We further propose construction heuristics and a hybrid metaheuristic approach with backtracking for solving larger instances. A sensitivity analysis for vehicle speed combinations reveals that increasing small autonomous vehicle (SAV) speeds has only very limited effects on cost. We therefore recommend to keep SAV speeds rather low because of a more pedestrian friendly environment in practical implementations.

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Section: Algorithm 1 Construction Heuristicmentioning

confidence: 99%

Two-echelon urban deliveries using autonomous vehicles

Puchinger

Sun

2020

Transportation Research Part E: Logistics and Transportation Re

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“…In order to solve the Bi‐PVRP‐SC, a dual‐phase Multi‐Start Multi‐objective Local Search (MSMLS) algorithm is proposed, see Braysy, Hasle, and Dullaert (2004) and Martí, Aceves, León, Moreno‐Vega, and Duarte (2019) where the authors use multi‐start local search algorithms to solve related single‐objective problems. In the first phase, feasible solutions are generated.…”

Section: Introductionmentioning

confidence: 99%

Optimizing a bi‐objective vehicle routing problem that appears in industrial enterprises

et al. 2020

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In this paper, a new solution method is implemented to solve a bi-objective variant of the vehicle routing problem that appears in industry and environmental enterprises. The solution involves designing a set of routes for each day in a period, in which the service frequency is a decision variable. The proposed algorithm, a muti-start multiobjective local search algorithm (MSMLS), minimizes total emissions produced by all vehicles and maximizes the service quality measured as the number of times that a customer is visited by a vehicle in order to be served. The MSMLS is a neighbourhood-based metaheuristic that obtains high-quality solutions and that is capable of achieving better performance than other competitive algorithms. Furthermore, the proposed algorithm is able to perform rapid movements thanks to the easy representation of the solutions.

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Batch Bayesian optimization via adaptive local search

2020

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The rapid proliferation of large language models (LLMs) such as GPT-4 and Gemini underscores the intense demand for resources during their training processes, posing significant challenges due to substantial computational and environmental costs. To alleviate this issue, we propose checkpoint merging in pretraining LLM. This method utilizes LLM checkpoints with shared training trajectories, and is rooted in an extensive search space exploration for the best merging weight via Bayesian optimization. Through various experiments, we demonstrate that: (1) Our proposed methodology exhibits the capacity to augment pretraining, presenting an opportunity akin to obtaining substantial benefits at minimal cost; (2) Our proposed methodology, despite requiring a given heldout dataset, still demonstrates robust generalization capabilities across diverse domains, a pivotal aspect in pretraining.

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Intelligent Multi-Start Methods

Cited by 6 publications

References 50 publications

Two-echelon urban deliveries using autonomous vehicles

Two-echelon urban deliveries using autonomous vehicles

Optimizing a bi‐objective vehicle routing problem that appears in industrial enterprises

Batch Bayesian optimization via adaptive local search

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