A partial evaluation approach for the School Bus Routing Problem

Article Computer Science, Artificial Intelligence

A metaheuristic for the rural school bus routing problem with bell adjustment

Douglas M. Miranda et al.

Summary: This paper discusses the school bus routing problem with bell adjustments, utilizing different strategies specifically designed for rural areas. The use of a memetic algorithm combining various search techniques resulted in significant cost savings, particularly for instances with fewer vehicles and more schools. Overall, the new strategy achieved up to 9% savings and 2.55% savings on consolidated results, showcasing its effectiveness in solving large scale instances.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

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Article Computer Science, Artificial Intelligence

Partial Evaluation Strategies for Expensive Evolutionary Constrained Optimization

Kamrul Hasan Rahi et al.

Summary: This article proposes a constraint handling strategy for expensive constrained optimization problems using partial evaluations, where constraints are evaluated in a sequence based on their likelihood of being violated and the evaluation is aborted if a constraint violation is encountered. The proposed algorithm is compared with several variants to establish the utility of its key components, and numerical experiments and benchmarking are conducted on a range of mathematical and engineering design problems to demonstrate its efficacy compared to state-of-the-art evolutionary optimization approaches.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2021)

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Article Computer Science, Artificial Intelligence

Ant Colony Optimization with Warm-Up

Mattia Neroni

Summary: Ant Colony Optimization (ACO) is a probabilistic technique inspired by ant behavior for solving computational problems. In this paper, a warm-up procedure for ACO is proposed, optimizing the initialization of the pheromone matrix to achieve the same or better results with fewer iterations.

ALGORITHMS (2021)

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Article Computer Science, Information Systems

Partial Evaluation and Efficient Discarding for the Maximal Covering Location Problem

Cynthia Porras et al.

Summary: The article introduces a more efficient version of the objective function for the maximal covering location problem, with experimental results showing that the best surrogate function is more than 5 times faster than the original function. This proposal allows for a more efficient metaheuristic solution.

IEEE ACCESS (2021)

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Article Computer Science, Information Systems