José Luis González-Velarde

TL;DR: In this paper, the authors present a heuristic approach to the multilevel generalized assignment problem (MGAP) which consists of a novel application of tabu search (TS), which employs neighborhoods defined by ejection chains, that produce moves of greater power without significantly increasing the computational effort.

TL;DR: A new algorithm based on a reduce and optimize approach and a new valid inequality is proposed to solve the multi-product multi-period inventory lot sizing with supplier selection problem and the developed heuristic algorithm outperforms the CPLEX MIP solver in both solution quality and computational time.

TL;DR: The computational experiments and the comparison with other solutions approaches presented in the related literature for tackling the TBAP show that the proposed algorithm is applicable to efficiently solve this difficult and essential container terminal problem.

TL;DR: This paper addresses a supply chain design problem based on a two-echelon single-product system and developed a metaheuristic algorithm that combines principles of greedy functions, Scatter Search, Path Relinking and Mathematical Programming to solve the problem.

TL;DR: This paper proposes a bi-objective programming model where dispersion and balancing with respect to the number of customers are used as performance criteria and proposes an improved e-constraint method for generating the optimal Pareto front.