Open AccessBook
Scheduling Algorithms
TLDR
Besides scheduling problems for single and parallel machines and shop scheduling problems, this book covers advanced models involving due-dates, sequence dependent changeover times and batching.Abstract:
Besides scheduling problems for single and parallel machines and shop scheduling problems, this book covers advanced models involving due-dates, sequence dependent changeover times and batching. Discussion also extends to multiprocessor task scheduling and problems with multi-purpose machines. Among the methods used to solve these problems are linear programming, dynamic programming, branch-and-bound algorithms, and local search heuristics. The text goes on to summarize complexity results for different classes of deterministic scheduling problems.read more
Citations
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Journal ArticleDOI
Resource-constrained project scheduling: Notation, classification, models, and methods
TL;DR: A classification scheme is provided, i.e. a description of the resource environment, the activity characteristics, and the objective function, respectively, which is compatible with machine scheduling and which allows to classify the most important models dealt with so far, and a unifying notation is proposed.
Journal ArticleDOI
A Formal Analysis and Taxonomy of Task Allocation in Multi-Robot Systems
Brian P. Gerkey,Maja J. Matarić +1 more
TL;DR: A domain-independent taxonomy of MRTA problems is given, and it is shown how many such problems can be viewed as instances of other, well-studied, optimization problems.
Journal ArticleDOI
An improved typology of cutting and packing problems
TL;DR: An improved typology of C&P problems is presented, which is partially based on Dyckhoff’s original ideas, but introduces new categorisation criteria, which define problem categories different from those of Dykhoff.
Book
Theory and practice of uncertain programming
TL;DR: This book provides a self-contained, comprehensive and up-to-date presentation of uncertain programming theory, including numerous modeling ideas, hybrid intelligent algorithms, and applications in system reliability design, project scheduling problem, vehicle routing problem, facility location problem, and machine scheduling problem.
Journal ArticleDOI
Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling
TL;DR: This paper shows how the performance of evolutionary multiobjective optimization (EMO) algorithms can be improved by hybridization with local search: the improvement in the convergence speed to the Pareto front and the increase in the computation time per generation.