The graph set T-colouring problem (GSTCP) generalises the classical graph colouring problem;it asks for the assignment of sets of integers to the vertices of a graph such that constraints on the separation of any two ...
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The graph set T-colouring problem (GSTCP) generalises the classical graph colouring problem;it asks for the assignment of sets of integers to the vertices of a graph such that constraints on the separation of any two numbers assigned to a single vertex or to adjacent vertices are satisfied and some objective function is optimised. Among the objective functions of interest is the minimisation of the difference between the largest and the smallest integers used (the span). In this article, we present an experimental study of localsearchalgorithms for solving general and large size instances of the GSTCP. We compare the performance of previously known as well as new algorithms covering both simple construction heuristics and elaborated stochastic local search algorithms. We investigate systematically different models and search strategies in the algorithms and determine the best choices for different types of instance. The study is an example of design of effective localsearch for constraint optimisation problems.
Automatic design of stochastic local search algorithms has been shown to be very effective in generating algorithms for the permutation flowshop problem for the most studied objectives including makespan, flowtime and...
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Automatic design of stochastic local search algorithms has been shown to be very effective in generating algorithms for the permutation flowshop problem for the most studied objectives including makespan, flowtime and total tardiness. The automatic design system uses a configuration tool to combine algorithmic components following a set of rules defined as a context-free grammar. In this paper we use the same system to tackle two of the most studied additional constraints for these objectives: sequence dependent setup times and no-idle constraint. Additional components have been added to adapt the system to the new problems while keeping intact the grammar structure and the experimental setup. The experiments show that the generated algorithms outperform the state of the art in each case.
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