Journal ArticleDOI
An Ant Colony Optimization Algorithm for Shop Scheduling Problems
Christian Blum,Michael Sampels +1 more
TLDR
An ant colony optimization approach that uses a strong non-delay guidance for constructing solutions and which employs black-box local search procedures to improve the constructed solutions is developed, which is the first competitive ant colonies optimization approach for job shop scheduling instances.Abstract:
We deal with the application of ant colony optimization to group shop scheduling, which is a general shop scheduling problem that includes, among others, the open shop scheduling problem and the job shop scheduling problem as special cases. The contributions of this paper are twofold. First, we propose a neighborhood structure for this problem by extending the well-known neighborhood structure derived by Nowicki and Smutnicki for the job shop scheduling problem. Then, we develop an ant colony optimization approach, which uses a strong non-delay guidance for constructing solutions and which employs black-box local search procedures to improve the constructed solutions. We compare this algorithm to an adaptation of the tabu search by Nowicki and Smutnicki to group shop scheduling. Despite its general nature, our algorithm works particularly well when applied to open shop scheduling instances, where it improves the best known solutions for 15 of the 28 tested instances. Moreover, our algorithm is the first competitive ant colony optimization approach for job shop scheduling instances.read more
Citations
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Journal ArticleDOI
Ant colony optimization theory: a survey
Marco Dorigo,Christian Blum +1 more
TL;DR: A survey on theoretical results on ant colony optimization, which highlights some open questions with a certain interest of being solved in the near future and discusses relations between ant colonies optimization algorithms and other approximate methods for optimization.
Journal ArticleDOI
Ant colony optimization for continuous domains
Krzysztof Socha,Marco Dorigo +1 more
TL;DR: This paper shows how ACO, which was initially developed to be a metaheuristic for combinatorial optimization, can be adapted to continuous optimization without any major conceptual change to its structure, and compares the results with those reported in the literature for other continuous optimization methods.
Journal ArticleDOI
Ant colony optimization: Introduction and recent trends
TL;DR: This work deals with the biological inspiration of ant colony optimization algorithms and shows how this biological inspiration can be transfered into an algorithm for discrete optimization, and presents some of the nowadays best-performing ant colonies optimization variants.
Book ChapterDOI
Swarm Intelligence in Optimization
Christian Blum,Xiaodong Li +1 more
TL;DR: This chapter focuses on two of the most successful examples of optimization techniques inspired by swarm intelligence: ant colony optimization and particle swarm optimization.
Journal ArticleDOI
Review of job shop scheduling research and its new perspectives under Industry 4.0
TL;DR: This paper explores the future research direction in SDS and discusses the new techniques for developing future new JSP scheduling models and constructing a framework on solving the JSP problem under Industry 4.0.
References
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Journal ArticleDOI
Ant system: optimization by a colony of cooperating agents
TL;DR: It is shown how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling, and the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.
Book
Practical Nonparametric Statistics
TL;DR: Probability Theory. Statistical Inference. Contingency Tables. Appendix Tables. Answers to Odd-Numbered Exercises and Answers to Answers to Answer Questions as discussed by the authors.
Journal ArticleDOI
MAX-MIN Ant system
Thomas Stützle,Holger H. Hoos +1 more
TL;DR: Computational results on the Traveling Salesman Problem and the Quadratic Assignment Problem show that MM AS is currently among the best performing algorithms for these problems.
Journal ArticleDOI
Benchmarks for basic scheduling problems
TL;DR: This paper proposes 260 randomly generated scheduling problems whose size is greater than that of the rare examples published, and the objective is the minimization of the makespan.
Book
The ant colony optimization meta-heuristic
Marco Dorigo,Gianni A. Di Caro +1 more
TL;DR: This chapter contains sections titled: Combinatorial Optimization, The ACO Metaheuristic, How Do I Apply ACO?