Author
Czesław Smutnicki
Other affiliations: University of Wrocław
Bio: Czesław Smutnicki is an academic researcher from Wrocław University of Technology. The author has contributed to research in topics: Job shop scheduling & Flow shop scheduling. The author has an hindex of 15, co-authored 67 publications receiving 2392 citations. Previous affiliations of Czesław Smutnicki include University of Wrocław.
Papers published on a yearly basis
Papers
More filters
TL;DR: A fast and easily implementable approximation algorithm for the problem of finding a minimum makespan in a job shop is presented, based on a taboo search technique with a specific neighborhood definition which employs a critical path and blocks of operations notions.
Abstract: A fast and easily implementable approximation algorithm for the problem of finding a minimum makespan in a job shop is presented. The algorithm is based on a taboo search technique with a specific neighborhood definition which employs a critical path and blocks of operations notions. Computational experiments up to 2,000 operations show that the algorithm not only finds shorter makespans than the best approximation approaches but also runs in shorter time. It solves the well-known 10 × 10 hard benchmark problem within 30 seconds on a personal computer.
964 citations
TL;DR: A fast and easily implementable approximation algorithm for the problem of finding a minimum makespan in the permutation flow shop is presented in this article, based on a tabu search technique with a specific neighborhood definition which employs a block of jobs.
443 citations
TL;DR: A new approximate algorithm is provided that is based on the big valley phenomenon, and uses some elements of so-called path relinking technique as well as new theoretical properties of neighbourhoods.
Abstract: The job shop scheduling problem with the makespan criterion is a certain NP-hard case from OR theory having excellent practical applications. This problem, having been examined for years, is also regarded as an indicator of the quality of advanced scheduling algorithms. In this paper we provide a new approximate algorithm that is based on the big valley phenomenon, and uses some elements of so-called path relinking technique as well as new theoretical properties of neighbourhoods. The proposed algorithm owns, unprecedented up to now, accuracy, obtainable in a quick time on a PC, which has been confirmed after wide computer tests.
289 citations
TL;DR: A fast and easily implementable approximation algorithm for the problem of finding a minimum makespan in a flow shop with parallel machines and a special advanced method of implementation improves the local search significantly and increases the speed of the algorithm.
168 citations
TL;DR: A new view on the solution space and the search process is provided, and a new approximate algorithm is proposed, which applies some properties of neighborhoods, refers to the big valley phenomenon, uses some elements of the scatter search as well as the path relinking technique.
83 citations
Cited by
More filters
Book•
[...]
TL;DR: This book explores the meta-heuristics approach called tabu search, which is dramatically changing the authors' ability to solve a host of problems that stretch over the realms of resource planning, telecommunications, VLSI design, financial analysis, scheduling, spaceplanning, energy distribution, molecular engineering, logistics, pattern classification, flexible manufacturing, waste management,mineral exploration, biomedical analysis, environmental conservation and scores of other problems.
Abstract: From the Publisher:
This book explores the meta-heuristics approach called tabu search, which is dramatically changing our ability to solve a hostof problems that stretch over the realms of resource planning,telecommunications, VLSI design, financial analysis, scheduling, spaceplanning, energy distribution, molecular engineering, logistics,pattern classification, flexible manufacturing, waste management,mineral exploration, biomedical analysis, environmental conservationand scores of other problems. The major ideas of tabu search arepresented with examples that show their relevance to multipleapplications. Numerous illustrations and diagrams are used to clarifyprinciples that deserve emphasis, and that have not always been wellunderstood or applied. The book's goal is to provide ''hands-on' knowledge and insight alike, rather than to focus exclusively eitheron computational recipes or on abstract themes. This book is designedto be useful and accessible to researchers and practitioners inmanagement science, industrial engineering, economics, and computerscience. It can appropriately be used as a textbook in a masterscourse or in a doctoral seminar. Because of its emphasis on presentingideas through illustrations and diagrams, and on identifyingassociated practical applications, it can also be used as asupplementary text in upper division undergraduate courses.
Finally, there are many more applications of tabu search than canpossibly be covered in a single book, and new ones are emerging everyday. The book's goal is to provide a grounding in the essential ideasof tabu search that will allow readers to create successfulapplications of their own. Along with the essentialideas,understanding of advanced issues is provided, enabling researchers togo beyond today's developments and create the methods of tomorrow.
6,373 citations
TL;DR: A survey of the nowadays most important metaheuristics from a conceptual point of view and introduces a framework, that is called the I&D frame, in order to put different intensification and diversification components into relation with each other.
Abstract: The field of metaheuristics for the application to combinatorial optimization problems is a rapidly growing field of research. This is due to the importance of combinatorial optimization problems for the scientific as well as the industrial world. We give a survey of the nowadays most important metaheuristics from a conceptual point of view. We outline the different components and concepts that are used in the different metaheuristics in order to analyze their similarities and differences. Two very important concepts in metaheuristics are intensification and diversification. These are the two forces that largely determine the behavior of a metaheuristic. They are in some way contrary but also complementary to each other. We introduce a framework, that we call the I&D frame, in order to put different intensification and diversification components into relation with each other. Outlining the advantages and disadvantages of different metaheuristic approaches we conclude by pointing out the importance of hybridization of metaheuristics as well as the integration of metaheuristics and other methods for optimization.
3,287 citations
22 Jun 2001
TL;DR: The development of a new complete solver, Chaff, is described which achieves significant performance gains through careful engineering of all aspects of the search-especially a particularly efficient implementation of Boolean constraint propagation (BCP) and a novel low overhead decision strategy.
Abstract: Boolean satisfiability is probably the most studied of the combinatorial optimization/search problems. Significant effort has been devoted to trying to provide practical solutions to this problem for problem instances encountered in a range of applications in electronic design automation (EDA), as well as in artificial intelligence (AI). This study has culminated in the development of several SAT packages, both proprietary and in the public domain (e.g. GRASP, SATO) which find significant use in both research and industry. Most existing complete solvers are variants of the Davis-Putnam (DP) search algorithm. In this paper we describe the development of a new complete solver, Chaff which achieves significant performance gains through careful engineering of all aspects of the search-especially a particularly efficient implementation of Boolean constraint propagation (BCP) and a novel low overhead decision strategy. Chaff has been able to obtain one to two orders of magnitude performance improvement on difficult SAT benchmarks in comparison with other solvers (DP or otherwise), including GRASP and SATO.
2,886 citations
01 Jan 1995
TL;DR: Computational bounds for local search in combinatorial local search algorithms for Combinatorial problems local searchgorithms for solving the combinatoric a dual local search framework for combinatorials the max-min ant system and local search for combinatorsial a framework for local combinatoria optimization problems localSearch in combinatorship optimization radarx heuristics and localsearch paginas.
Abstract: computational bounds for local search in combinatorial local search algorithms for combinatorial problems local search algorithms for solving the combinatorial a dual local search framework for combinatorial the max-min ant system and local search for combinatorial a framework for local combinatorial optimization problems local search in combinatorial optimization mifou local search in combinatorial optimization radarx heuristics and local search paginas.fe.up local search in combinatorial optimization banani local search in combinatorial optimization integrating interval estimates of global optima and local local search in combinatorial optimization holbarto a fuzzy valuation-based local search framework for local search in combinatorial optimization gbv gentle introduction to local search in combinatorial e cient local search for several combinatorial introduction: combinatorial problems and search on application of the local search optimization online local search for combinatorial optimisation problems how to choose solutions for local search in multiobjective a hybrid of inference and local search for distributed on set-based local search for multiobjective combinatorial localsolver: black-box local search for combinatorial on local optima in multiobjective combinatorial sets of interacting scalarization functions in local introduction e r optimization online estimation-based local search for stochastic combinatorial advanced search combinatorial problems sas/or user's guide: local search optimization how easy is local search? univerzita karlova metaheuristic search for combinatorial optimization local search genetic algorithms for the job shop towards a formalization of combinatorial local search dynamic and adaptive neighborhood search in combinatorial global search in combinatorial optimization using a framework for the development of local search heuristics a feasibility-preserving local search operator for hybrid metaheuristics in combinatorial optimization: a survey consultant-guided search algorithms with local search for a new optimization algorithm for combinatorial problems hybrid metaheuristics in combinatorial optimization: a survey network algorithms colorado state university model-based search for combinatorial optimization: a local and global optimization stochastic local search algorithms for multiobjective corso (collaborative reactive search optimization local search in combinatorial optimization zaraa
1,055 citations
TL;DR: This work presents a new iterated greedy algorithm that applies two phases iteratively, named destruction, were some jobs are eliminated from the incumbent solution, and construction, where the eliminated jobs are reinserted into the sequence using the well known NEH construction heuristic.
923 citations