A Machine Assignment Mechanism for Compile-Time List-Scheduling Heuristics

Finding an optimal solution for a scheduling problem is NP-complete. Therefore, it is necessary to use heuristics to find a good schedule rather than evaluating all possible schedules. List scheduling is generally accepted as an attractive approach, since it combines low complexity with good results. List scheduling consists of two phases: a task prioritization phase where a certain priority is computed and assigned to each task, and a machine assignment phase where each task (in order of its priority) is assigned a machine that minimizes a suitable cost function. This paper presents a machine assignment mechanism that can be used with any list-scheduling algorithm. The mechanism is called Reverse Duplicator Mechanism and outperforms the current mechanisms

Meta-Heuristic Solution in RCPSP

Tato práce se zabývá popisem stavu resource-constrained project scheduling problem. Definuje základní problém a jeho složitost. Také popisuje varianty tohoto problému. Jsou představeny algoritmy pro řešení RCPSP. V práci je důkladně rozebrán heuristický genetický algoritmus GARTH. Je také naznačena implementace dvou prototypů řešících RCPSP pomocí algoritmu GARTH. Je navrhnuto několik vylepšení originálního algoritmu a ty jsou vyhodnoceny.This thesis deals with the description of the state of resource-constrained project scheduling problem. It defines the formal problem and its complexity. It also describes variants of this problem. Algorithms for solving RCPSP are presented. Heuristic genetic algorithm GARTH is analyzed in depth. The implementation of prototypes solving RCPSP using GARTH is outlined. Several improvements to the original algorithm are designed and evaluated.

Reactive scheduling to treat disruptive events in the MRCPSP

Esta tesis se centra en diseñar y desarrollar una metodología 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 metaheurísticas: (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 metaheurísticos propuestos sobre otros enfoques heurísticos y metaheurísticos del estado del arte. A partir de los estudios experimentales se ha ajustado la MBFO, utilizando un caso de estudio.DoctoradoDoctor en Ingeniería Industria

Safe Specification of Operator Precedence Rules

International audienceIn this paper we present an approach to specifying opera- tor precedence based on declarative disambiguation constructs and an implementation mechanism based on grammar rewriting. We identify a problem with existing generalized context-free parsing and disambigua- tion technology: generating a correct parser for a language such as OCaml using declarative precedence specification is not possible without resorting to some manual grammar transformation. Our approach provides a fully declarative solution to operator precedence specification for context-free grammars, is independent of any parsing technology, and is safe in that it guarantees that the language of the resulting grammar will be the same as the language of the specification grammar. We evaluate our new approach by specifying the precedence rules from the OCaml reference manual against the highly ambiguous reference grammar and validate the output of our generated parser

Strong Bounds for Resource Constrained Project Scheduling: Preprocessing and Cutting Planes

Resource Constrained Project Scheduling Problems (RCPSPs) without preemption are well-known NP-hard combinatorial optimization problems. A feasible RCPSP solution consists of a time-ordered schedule of jobs with corresponding execution modes, respecting precedence and resources constraints. In this paper, we propose a cutting plane algorithm to separate five different cut families, as well as a new preprocessing routine to strengthen resource-related constraints. New lifted versions of the well-known precedence and cover inequalities are employed. At each iteration, a dense conflict graph is built considering feasibility and optimality conditions to separate cliques, odd-holes and strengthened Chv\'atal-Gomory cuts. The proposed strategies considerably improve the linear relaxation bounds, allowing a state-of-the-art mixed-integer linear programming solver to find provably optimal solutions for 754 previously open instances of different variants of the RCPSPs, which was not possible using the original linear programming formulations.Comment:

Mixed-integer linear programming based approaches for the resource constrained project scheduling problem.

Programa de P?s-Gradua??o em Ci?ncia da Computa??o. Departamento de Ci?ncia da Computa??o, Instituto de Ci?ncias Exatas e Biol?gicas, Universidade Federal de Ouro Preto.Resource Constrained Project Scheduling Problems (RCPSPs) without preemption are well-known NP-hard combinatorial optimization problems. A feasible RCPSP solution consists of a time-ordered schedule of jobs with corresponding execution modes, respecting precedence and resources constraints. First, in this thesis, we provide improved upper bounds for many hard instances from the literature by using methods based on Stochastic Local Search (SLS). As the most contribution part of this work, we propose a cutting plane algorithm to separate five different cut families, as well as a new preprocessing routine to strengthen resource-related constraints. New lifted versions of the well-known precedence and cover inequalities are employed. At each iteration, a dense conict graph is built considering feasibility and optimality conditions to separate cliques, odd-holes and strengthened Chv?tal-Gomory cuts. The proposed strategies considerably improve the linear relaxation bounds, allowing a state-of-the-art mixed-integer linear programming solver to nd provably optimal solutions for 754 previously open instances of different variants of the RCPSPs, which was not possible using the original linear programming formulations