[en] This paper presents firstly a dynamic grouping maintenance strategy for multi-component systems with positive economic dependence, which implies that combining maintenance activities is cheaper than performing maintenance on components separately. Preventive maintenance durations and multiple occurrences of maintenance activities within scheduling horizon are considered. Moreover, in a dynamic context, maintenance opportunities, defined as inactivity periods of the systems at which several maintenance activities could be executed with reduced maintenance costs, may randomly occur with time. The second objective of the paper is to propose a new algorithm to optimally update online the grouped maintenance planning by taking into account the maintenance opportunities. A numerical example of a five components system is finally introduced to illustrate the proposed dynamic grouping maintenance strategy

[en] This paper addresses minimizing Tardy/Lost penalties with common due dates on a single machine. According to this penalty criterion, if tardiness of a job exceeds a predefined value, the job will be lost and penalized by a fixed value. The problem is formulated as an integer programming model, and a heuristic algorithm is constructed. Then, using the proposed dominance rules and lower bounds, we develop two dynamic programming algorithms as well as a branch and bound. Experimental results show that the heuristic algorithm has an average optimality gap less than 2 % in all problem sizes. Instances up to 250 jobs with low variety of process times are optimally solved and for high process time varieties, the algorithms solved all instances up to 75 jobs.

[en] The study of infinite-horizon nonstationary dynamic programs using the operator approach is continued. The point of view here differs slightly from that taken by others, in that Denardo's local income function is not used as a starting point. Infinite-horizon values are defined as limits of finite-horizon values, as the horizons get long. Two important conditions of an earlier paper are weakened, yet the optimality equations, the optimality criterion, and the existence of optimal ''structured'' strategies are still obtained

[en] The rapid expansion of nuclear programmes for the future implies a strong growth in the enrichment market and the need to plan capacity increases to meet the new requirements. This article deals more specifically with increased output from an existing plant, of which the characteristics were optimized earlier on the basis of a production goal and of the economic conditions at the time. The solution in such a case is either to modify the equipment already installed in the plant or to install extra equipment, optimizing its internal parameters as a function of the amount of separation work required and of its lay-out in the original plant or in a new plant

[en] Short communication

[en] We develop a martingale approach for continuous-time stochastic control with discretionary stopping. The relevant Dynamic Programming Equation and Maximum Principle are presented. Necessary and sufficient conditions are provided for the optimality of a control strategy; these are analogues of the 'equalization' and 'thriftiness' conditions introduced by Dubins and Savage (1976) in a related, discrete-time context. The existence of a thrifty control strategy is established

[en] In this paper, a multiple optical line terminal (OLT) passive optical network (PON) and the dynamic programming algorithm for downstream channel is proposed. By wavelength-selectable module, the adjustable remote node (RN) is constructed. By this adjustable RN, a simple and efficient multi-OLT PON is designed. By the way of first-plan and then-load, optical network unit (ONU) groups are established in order to realize the fast loading of ONUs. Specially, by introducing dynamic programming algorithm, the wavelength bandwidth utilization is maximized. Finally, by the simulation and analysis, the effectiveness of the proposed scheme is demonstrated.

[en] Motivated by the work of Fleming, we provide a general framework to associate inf-sup type values with the Isaacs equations.We show that upper and lower bounds for the generators of inf-sup type are upper and lower Hamiltonians, respectively. In particular, the lower (resp. upper) bound corresponds to the progressive (resp. strictly progressive) strategy. By the Dynamic Programming Principle and identification of the generator, we can prove that the inf-sup type game is characterized as the unique viscosity solution of the Isaacs equation. We also discuss the Isaacs equation with a Hamiltonian of a convex combination between the lower and upper Hamiltonians

[en] This paper summarizes major aspects of supporting systems dynamics modelling and simulation by knowledge-based systems or expert systems, respectively. Combinations of numerical simulation and symbolic knowledge processing techniques have proved to be very useful for improving the adequate representation of system knowledge, the efficiency, flexibility and consistency of models and the support and advice of users in system modelling. Based on actual requirements concerning the synthesis and experimental application of symbolic models, basic architectures and features of knowledge-based modelling environments are discussed. Results of prototype implementations are presented supporting the hierarchical description of discrete systems and the model synthesis in the domain of computer systems. (orig.)

[en] A new statistical approach to alignment (finding the longest common subsequence) of two random RNA-type sequences is proposed. We have constructed a generalized 'dynamic programming' algorithm for finding the extreme value of the free energy of two noncoding RNAs. In our procedure, we take into account the binding free energy of two random heteropolymer chains which are capable of forming the cloverleaf-like spatial structures typical for RNA molecules. The algorithm is based on two observations: (i) the standard alignment problem can be considered as a zero-temperature limit of a more general statistical problem of binding of two associating heteropolymer chains; (ii) this last problem can be generalized naturally to consider sequences with hierarchical cloverleaf-like structures (i.e. of RNA type). The approach also permits us to perform a 'secondary structure recovery'. Namely, we can predict the optimal secondary structures of interacting RNAs in a zero-temperature limit knowing only their primary sequences.