This study proposed multipath architecture for a dynamic (DP) programming approach to solve the problem of the uncertain starting points in dynamic programming. The starting points of those paths are selected from the local maximum of onset detection function and beginning interval of excerpts. We also utilize the tempi of tempo estimation to give the guidance of the beat tracking. Index Terms ...

This paper considers generation self-scheduling in electricity markets under uncertain price. Based on the robust optimization denoted as RO methodology, a new self-scheduling model, which has a complicated max-min optimization structure, is set up. By using optimal dual theory, the proposed model is reformulated to an ordinary quadratic and quadratic cone programming problems in the cases of b...

An uncertain economic order quantity (UEOQ) model with payment in advance is developed to purchase high-price raw materials. A joint policy of replenishments and pre-payments is employed to supply the materials. The rate of demand is considered LR-fuzzy variables, lead-time is taken to be constant, and it is assumed that shortage does not occur in the cycles. The cycle is divided into three par...

Optimal solutions of Linear Programming problems may become severely infeasible if the nominal data is slightly perturbed. We demonstrate this phenomenon by studying 90 LPs from the well-known NETLIB collection. We then apply the Robust Optimization methodology (Ben-Tal and Nemirovski [1-3]; El Ghaoui et al. [5,6]) to produce “robust” solutions of the above LPs which are in a sense immuned agai...

We address a class of planning problems where the optimization decisions influence the time of information discovery for a subset of the uncertain parameters. The standard stochastic programming approach cannot be used for these problems. We present a hybrid mixed-integer disjunctive programming formulation and a Lagrangean duality based branch and bound algorithm for these problems and illustr...

Sometimes a complex stochastic decision system undertakes multiple tasks called events, and the decision-maker wishes to maximize the chance functions which are defined as the probabilities of satisfying these events. Originally introduced by Liu and Iwamura [6], dependent-chance programming is aimed at maximizing some chance functions of events in an uncertain environment. In this work we show...

The risk management for virtual enterprise is the hot research area recently. There is always lack of historical data and there are many uncertain factors in virtual enterprise. Hence, in this paper, the fuzzy synthetic evaluation embedded nonlinear integer programming model of the risk programming for virtual enterprise is established according to the characteristics of virtual enterprise and ...

Cell formation (CF) problem is one of the most important decision problems in designing a cellular manufacturing system includes grouping machines into machine cells and parts into part families. Several factors should be considered in a cell formation problem. In this work, robust optimization of a mathematical model of a dynamic cell formation problem integrating CF, production planning and w...

Abstract In Sweden, as in many other countries, programming has been added to the curriculum recent years. This paper explores how and under what conditions is transformed into teaching technology education. Teachers grade 7–9 were interviewed about they teach context of education, influenced choices made. Data was analysed using content analysis. The results suggest that teachers mainly see a ...