Job shop scheduling problem is one of the most important problems in the combinatorial optimization problems and it is applied to various fields about engineering. Many works have been reported for this problem using Genetic Algorithm (GA). The GA is one of the most powerful optimization methods based on the mechanics of natural evolution. In this paper, we propose a new algorithm for the job s...

The indeterministic multi-layer job-shop scheduling problem, which is the extension of the traditional job-shop scheduling, is introduced in this paper. The framework and some key issues of the problem are discussed. A multi-agent reinforcement learning approach, named memory-evolution-based MAS reinforcement learning algorithm, is breifly introduced too. Experiment results show that our approa...

A data mining based approach to discover previously unknown priority dispatching rules for job shop scheduling problem is presented. This approach is based upon seeking the knowledge that is assumed to be embedded in the efficient solutions provided by the optimization module built using tabu search. The objective is to discover the scheduling concepts using data mining and hence to obtain a ru...

Proactive scheduling seeks to generate high quality solutions despite execution time uncertainty. Building on work in [Beck and Wilson, 2004], we conduct an empirical study of a number of algorithms for the job shop scheduling problem with probabilistic durations. The main contributions of this paper are: the introduction and empirical analysis of a novel constraint-based search technique that ...

Practical Constraint Satisfaction Problems (CSPs) such as design of integrated circuits or scheduling generally entail large search spaces with hundreds or even thousands of variables, each with hundreds or thousands of possible values. Often, only a very tiny fraction of all these possible assignments participates in a satisfactory solution. This article discusses techniques that aim at reduci...

this paper investigates the problem of just-in-time permutation flow shop scheduling with limited buffers and linear job deterioration in an uncertain environment. the fuzzy set theory is applied to describe this situation. a novel mixed-integer nonlinear program is presented to minimize the weighted sum of fuzzy earliness and tardiness penalties. due to the computational complexities, the prop...