Some aspects of scatter search in the flow-shop problem

Nowicki, Eugeniusz; Smutnicki, Czesław

doi:10.1016/j.ejor.2004.08.021

Cited by 80 publications

(31 citation statements)

References 19 publications

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“…(Corberen 2002;Nowicki and Smutnicki 2006;Siepak and Jozefczyk 2011;Xu et al 2000). The applications of this algorithm to the uncertain version of the various scheduling problems were presented in (Siepak and Jozefczyk 2013).…”

Section: Ss Heuristicsmentioning

confidence: 99%

Solution algorithms for unrelated machines minmax regret scheduling problem with interval processing times and the total flow time criterion

Siepak

Józefczyk

2014

Ann Oper Res

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An uncertain version of the task scheduling problem on unrelated machines to minimize the total flow time is considered. It is assumed that processing times are not known a priori, but they belong to intervals of known bounds. The absolute regret is applied to evaluate the uncertainty, and minmax regret task scheduling problem is solved. A simple 2-approximate middle intervals time efficient algorithm is proposed. More time consuming but better in terms of the quality of solutions scatter search based heuristic algorithm is described. Its usefulness is justified via computational experiments.

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Section: Ss Heuristicsmentioning

confidence: 99%

Solution algorithms for unrelated machines minmax regret scheduling problem with interval processing times and the total flow time criterion

Siepak

Józefczyk

2014

Ann Oper Res

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“…Skipping consciously the long list of papers dealing with this subject we only refer the reader to the recent reviews and the best up-to-now algorithms [5,6].…”

Section: Permutation Flow Shop Problemmentioning

confidence: 99%

“…This work constitutes the continuation of authors research on constructing efficient algorithms applied to solve hard combinatorial problems ( [2,5,6]). …”

Section: Introductionmentioning

confidence: 99%

Parallel Calculating of the Goal Function in Metaheuristics Using GPU

Bożejko

Smutnicki

Uchroński

2009

Lecture Notes in Computer Science

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Abstract. We consider a metaheuristic optimization algorithm which uses single process (thread) to guide the search through the solution space. Thread performs in the cyclic way (iteratively) two main tasks: the goal function evaluation for a single solution or a set of solutions and management (solution filtering and selection, collection of history, updating). The latter task takes statistically 1-3% total iteration time, therefore we skip its acceleration as useless. The former task can be accelerated in parallel environments in various manners. We propose certain parallel small-grain calculation model providing the cost optimal method. Then, we carry out an experiment using Graphics Processing Unit (GPU) to confirm our theoretical results.

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“…The flow shop problem can be defined as follows, using the notation of Nowicki, Smutnicki [1] and Grabowski, Wodecki [2] as a proper one for the problem considered. There are: a set of n jobs J = {1,2,...,«} and a set of m machines M = {1,2, ...,m}.…”

Section: The Flow Shop Problemmentioning

confidence: 99%