3 research outputs found
An Iterative Path-Breaking Approach with Mutation and Restart Strategies for the MAX-SAT Problem
Although Path-Relinking is an effective local search method for many
combinatorial optimization problems, its application is not straightforward in
solving the MAX-SAT, an optimization variant of the satisfiability problem
(SAT) that has many real-world applications and has gained more and more
attention in academy and industry. Indeed, it was not used in any recent
competitive MAX-SAT algorithms in our knowledge. In this paper, we propose a
new local search algorithm called IPBMR for the MAX-SAT, that remedies the
drawbacks of the Path-Relinking method by using a careful combination of three
components: a new strategy named Path-Breaking to avoid unpromising regions of
the search space when generating trajectories between two elite solutions; a
weak and a strong mutation strategies, together with restarts, to diversify the
search; and stochastic path generating steps to avoid premature local optimum
solutions. We then present experimental results to show that IPBMR outperforms
two of the best state-of-the-art MAX-SAT solvers, and an empirical
investigation to identify and explain the effect of the three components in
IPBMR
Multi-Objective Multi-mode Time-Cost Tradeoff modeling in Construction Projects Considering Productivity Improvement
In today's construction industry, poor performance often arises due to
various factors related to time, finances, and quality. These factors
frequently lead to project delays and resource losses, particularly in terms of
financial resources. This research addresses the Multimode Resource-Constrained
Project Scheduling Problem (MRCPSP), a real-world challenge that takes into
account the time value of money and project payment planning. In this context,
project activities exhibit discrete cost profiles under different execution
conditions and can be carried out in multiple ways. This paper aims to achieve
two primary objectives: minimizing the net present value of project costs and
project completion times while simultaneously improving the project's
productivity index. To accomplish this, a mathematical programming model based
on certain assumptions is proposed. Several test cases are designed, and they
are rigorously evaluated using the methodology outlined in this paper to
validate the modeling approach. Recognizing the NP-hard nature of this problem,
a multi-objective genetic algorithm capable of solving large-scale instances is
developed. Finally, the effectiveness of the proposed solution is assessed by
comparing it to the performance of the NSGA-II algorithm using well-established
efficiency metrics. Results demonstrate the superior performance of the
algorithm introduced in this study.Comment: 40 pages, 20 figures, 7 table
Reactive scheduling to treat disruptive events in the MRCPSP
Esta tesis se centra en diseñar y desarrollar una metodologÃa para abordar el MRCPSP con diversas funciones objetivo y diferentes tipos de interrupciones. En esta tesis se exploran el MRCPSP con dos funciones objetivo, a saber: (1) minimizar la duración del proyecto y (2) maximizar el valor presente neto del proyecto. Luego, se tiene en cuenta dos tipos diferentes de interrupciones, (a) interrupción de duración, e (b) interrupción de recurso renovable. Para resolver el MRCPSP, en esta tesis se proponen tres estrategias metaheurÃsticas: (1) algoritmo memético para minimizar la duración del proyecto, (2) algoritmo adaptativo de forrajeo bacteriano para maximizar el valor presente neto del proyecto y (3) algoritmo de optimización multiobjetivo de forrajeo bacteriano (MBFO) para resolver el MRCPSP con eventos de interrupción. Para juzgar el rendimiento del algoritmo memético y de forrajeo bacteriano propuestos, se ha llevado a cabo un extenso análisis basado en diseño factorial y diseño Taguchi para controlar y optimizar los parámetros del algoritmo. Además se han puesto a prueba resolviendo las instancias de los conjuntos más importantes en la literatura: PSPLIB (10,12,14,16,18,20 y 30 actividades) y MMLIB (50 y 100 actividades). También se ha demostrado la superioridad de los algoritmos metaheurÃsticos propuestos sobre otros enfoques heurÃsticos y metaheurÃsticos del estado del arte. A partir de los estudios experimentales se ha ajustado la MBFO, utilizando un caso de estudio.DoctoradoDoctor en IngenierÃa Industria