Reinaldo J. Moraga

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The problem addressed in this paper is the non-preemptive unrelated parallel machine scheduling problem with the objective of minimizing the makespan. Machine-dependent and job sequence-dependent setup times are considered, all jobs are available at time zero, and all times are deterministic. This is a NP-hard problem and in this paper, optimal solutions(More)
Effectively managing a supply chain requires visibility to detect unexpected variations in the dynamics of the supply chain environment at an early stage. This paper proposes a methodology that captures the dynamics of the supply chain, predicts and analyzes future behavior modes, and indicates potentials for modifications in the supply chain parameters in(More)
As the size, complexity, and functionality of systems to model and simulate continue to increase, benefits such as interoperability and reusability enabled by distributed discrete-event simulation are of interest, especially for distributed manufacturing and enterprise engineering. The High Level Architecture (HLA), a standard distributed simulation(More)
This paper introduces an interesting meta-heuristic called Meta-RaPS (Meta-heuristic for Randomized Priority Search) for solving combinatorial problems . Meta-RaPS incorporates randomness within priority rules to construct a feasible solution at each iteration. In addition, Meta-RaPS includes improvement heuristics for enhancing the feasible solution(More)
This paper presents a new meta heuristic algorithm based on the search method called simulated annealing, and its application to solving multi objective simulation optimization problems. Since the simulated annealing search method has been extensively applied as a modern heuristic to solve single objective simulation optimization problems, a modification to(More)
This work shows an object oriented library that was designed to facilitate the development of simulation studies of sawmills. A group technology approach was used to minimize the number of objects in the library, which includes objects that have the functionality of the equipments found in these facilities, so that the analyst only needs to provide the(More)
This paper introduces a new method that facilitates the stability analysis of system dynamics models. The method is based on the concepts of asymptotic stability and Accumulated Deviations from Equilibrium (ADE) convergence. We prove several theorems that show that ADE convergence of a state variable will make its trajectory approach asymptotic stability.(More)
Using outputs of a supply chain system dynamics model, neural networks’ pattern recognition capabilities and eigen value analysis are utilised to detect and analyse behavioural changes in the supply chain and predict their impact in the shortand long-term horizons on performances. Neural networks are used to detect changes in the supply chain behaviour at a(More)