Hu et al. [“A boundary problem for group testing”, SIAM J. Algebraic Discrete Meth.2 (1981), 81–87] conjectured that the minimax test number to find d defectives in 3d items is 3d−1, a surprisingly difficult combinatorial problem about which very little is known. In this article we state three more conjectures and prove that they are all equivalent to the conjecture of Hu et al. Notably, as a byproduct, we also obtain an interesting upper bound for M(d,n).

This paper describes a new representation for the solutions of the resource-constrained project scheduling problem (RCPSP) denoted Activity Set List. The most efficient heuristics for the problem use the activity list representation and the serial SGS method to construct the corresponding solution (schedule). The activity list may induce a search space of representations much larger then the space of schedules because the same schedule can correspond to many different activity list representations. We indicate how the activity set list representation can significantly reduce the search space, and how to move more efficiently through it. Furthermore, this new representation never excludes the optimal solution and it has many interesting properties. An evaluation of the search space reduction induced by this representation is made for the most used library of instances in the literature. The activity set list representation may be used to construct a new category of more efficient solution procedures for the problem.

In this work, we present an introduction to automatic differentiation,its use in optimization software, and some new potential usages. Wefocus on the potential of this technique inoptimization. We do not dive deeply in the intricacies of automaticdifferentiation, but put forward its key ideas. We sketch a survey, asof today, of automatic differentiation software, but warn the readerthat the situation with respect to software evolves rapidly. In thelast part of the paper, we present some potential future usage ofautomatic differentiation, assuming an ideal tool is available, whichwill become true in some unspecified future.

In this paper we introduce a set of orthonormal functions, , where ϕn[r] is composed of a sine function and a sigmoidal transformation γr of order r>0. Based on the proposed functions ϕn[r] named by sigmoidal sine functions, we consider a series expansion of a function on the interval [−1,1] and the related convergence analysis. Furthermore, we extend the sigmoidal transformation to the whole real line ℝ and then, by reconstructing the existing sigmoidal cosine functions ψn[r] and the presented functions ϕn[r], we develop two kinds of 2-periodic series expansions on ℝ. Superiority of the presented sigmoidal-type series in approximating a function by the partial sum is demonstrated by numerical examples.

An important task of knowledge discovery deals with discovering association rules. This very general model has been widely studied and efficient algorithms have been proposed. But most of the time, only frequent rules are seeked. Here we propose to consider this problem as a multi-objective combinatorial optimization problem in order to be able to also find non frequent but interesting rules. As the search space may be very large, a discussion about different approaches is proposed and a hybrid approach that combines a metaheuristic and an exact operator is presented.

Quintic B-spline collocation schemes for numerical solution of the regularized long wave (RLW) equation have been proposed. The schemes are based on the Crank–Nicolson formulation for time integration and quintic B-spline functions for space integration. The quintic B-spline collocation method over finite intervals is also applied to the time-split RLW equation and space-split RLW equation. After stability analysis is applied to all the schemes, the results of the three algorithms are compared by studying the propagation of the solitary wave, interaction of two solitary waves and wave undulation.

We describe a simple deterministic model for the dispersion of particulate ash which has been ejected into the atmosphere by a volcanic eruption. In our model the atmosphere is divided into a series of horizontal layers within which the physical parameters involved are constant. This is an effective way to allow for the changing behaviour of the particulate ash and atmospheric flow with height whilst retaining simplicity. From our model we construct an analytical expression for the final deposit which could be incorporated within hazard assessment projections. In particular we show how to allow for variation with height of dispersion (caused by turbulence due to the wind) and settling speed (affected by the agglomeration and fragmentation of particles).

In this paper a smoothed particle hydrodynamics (SPH) method is introduced for simulating two-dimensional incompressible non-Newtonian fluid flows, and the non-Newtonian effects in the flow of a fluid which can be modelled by generalized Newtonian constitutive equations are investigated. Two viscoplastic models including Bingham-plastic and power-law models are considered along with the Newtonian model. The governing equations include the conservation of mass and momentum equations in a pseudo-compressible form. The spatial discretization of these equations is achieved by using the SPH method. The temporal discretization algorithm is a fully explicit two-step predictor–corrector scheme. In the prediction step, an intermediate velocity field is obtained using a forward scheme in time without enforcing incompressibility. The correction step consists of solving a pressure Poisson equation to satisfy incompressibility by providing a trade-off between the pressure and density variables. The performance of the proposed scheme is evaluated by studying a benchmark problem including flow of viscoplastic fluids in a lid-driven cavity. Both Newtonian and non-Newtonian cases are investigated and the results are compared with available numerical data. It was shown that in all cases the method is stable and the results are in very good agreement with available data.

Families of vortex equilibria, with constant vorticity, in steady flow past a flat plate are computed numerically. An equilibrium configuration, which can be thought of as a desingularized point vortex, involves a single symmetric vortex patch located wholly on one side of the plate. Given that the outermost edge of the vortex is unit distance from the plate, the equilibria depend on three parameters: the length of the plate, circulation about the plate, and the distance of the innermost edge of the vortex from the plate. Families in which there is zero circulation about the plate and for which the Kutta condition at the plate ends is satisfied are both considered. Properties such as vortex area, lift and free-stream speed are computed. Time-dependent numerical simulations are used to investigate the stability of the computed steady solutions.

In this paper, by using the Leggett–Williams fixed point theorem, we prove the existence of three nonnegative solutions to second-order nonlinear impulsive differential equations with a three-point boundary value problem.

A sharp L2 inequality of Ostrowski type is established, which provides a generalization of some previous results and gives some other interesting results as special cases. Applications in numerical integration are also given.

This paper presents a migration strategy for a set of mobile agents (MAs) in order to satisfy customers' requests in a transport network, through a multimodal information system. In this context, we propose an optimization solution which operates on two levels. The first one aims to constitute a set of MAs building their routes, called Workplans. At this level, Workplans must incorporate all nodes, representing information providers in the multimodal network, in order to explore it completely. Thanks to an evolutionary approach, the second level must optimize nodes selection in order to increase the number of satisfied users. The assignment of network nodes to the required services must be followed by a Workplan update procedure in order to deduce final routes paths. Finally, simulation results are mentioned to invoke the different steps of our adopted approach.

We present in this paper a new multiobjective memetic algorithm scheme called MEMOX. In current multiobjective memetic algorithms, the parents used for recombination are randomly selected. We improve this approach by using a dynamic hypergrid which allows to select a parent located in a region of minimal density. The second parent selected is a solution close, in the objective space, to the first parent. A local search is then applied to the offspring. We experiment this scheme with a new multiobjective tabu search called PRTS, which leads to the memetic algorithm MEMOTS. We show on the multidimensional multiobjective knapsack problem that if the number of objectives increase, it is preferable to have a diversified research rather using an advanced local search. We compare the memetic algorithm MEMOTS to other multiobjective memetic algorithms by using different quality indicators and show that the performances of the method are very interesting.

In this paper, a new approach to a characterization of solvability of a nonlinear nonsmooth multiobjective programming problem with inequality constraints is introduced. A family of η-approximated vector optimization problems is constructed by a modification of the objective and the constraint functions in the original nonsmooth multiobjective programming problem. The connection between (weak) efficient points in the original nonsmooth multiobjective programming problem and its equivalent η-approximated vector optimization problems is established under V-invexity. It turns out that, in most cases, solvability of a nonlinear nonsmooth multiobjective programming problem can be characterized by solvability of differentiable vector optimization problems.

By means of a symbolic calculus for finding solutions of difference equations, we derive explicit eigenvalues, eigenvectors and inverses for tridiagonal Toeplitz matrices with four perturbed corners.

We present here a pricing model which is an extension of the cooperative game concept and which includes a notion of elastic demand. We present some existence results as well as an algorithm, and we conclude by discussing a specific problem related to network pricing.

We present an inexact interior point proximal method to solve linearly constrained convex problems. In fact, we derive a primal-dual algorithm to solve the KKT conditions of the optimization problem using a modified version of the rescaled proximal method. We also present a pure primal method. The proposed proximal method has as distinctive feature the possibility of allowing inexact inner steps even for Linear Programming. This is achieved by using an error criterion that bounds the subgradient of the regularized function, instead of using ϵ-subgradients of the original objective function. Quadratic convergence for LP is also proved using a more stringent error criterion.

The recourse to operation research solutions has strongly increasedthe performances of scheduling task in the High-Level Synthesis(called hardware compilation). Scheduling a whole program is notpossible as too many constraints and objectives interact. We decomposehigh-level scheduling in three steps. Step 1: Coarse-grain schedulingtries to exploit parallelism and locality of the whole program (inparticular in loops, possibly imperfectly nested) with a rough view ofthe target architecture. This produces a sequence of logical steps,each of which contains a pool of macro-tasks. Step 2: Micro-schedulingmaps and schedules each macro-task independently taking into accountall peculiarities of the target architecture. This produces areservation table for each macro-task. Step 3: Fine-grain schedulingrefines each logical step by scheduling all its macro-tasks. Thispaper focuses on the third step.As tasks are modeled as reservation tables, we can express resourceconstraints using dis-equations (i.e., negations of equations). Asmost scheduling problems, scheduling tasks with reservation tables tominimize the total duration is NP-complete. Our goal here is todesign different strategies and to evaluate them, on practicalexamples, to see if it is possible to find optimal solution inreasonable time. The first algorithm is based on integer linearprogramming techniques for scheduling, which we adapt to our specificproblem. Our main algorithmic contribution is an exactbranch-and-bound algorithm, where each evaluation is accelerated byvariant of Dijkstra's algorithm. A simple greedy heuristic is alsoproposed for comparisons. The evaluation and comparison are done onpieces of scientific applications from the PerfectClub and theHLSynth95 benchmarks. The results demonstrate the suitability of thesesolutions for high-level synthesis scheduling.

Minimizing shutterings assembling time on construction sites can yield significant savings in labor costs and crane moves. It requires solving a pairing problem that optimizes the ability for the crane to move chains of shutterings as a whole when they can be later reused together to frame another wall of the site. In this paper, we show that this problem is NP-hard in the strong sense as well as both its multiflow and ordering aspects. We also introduce a linear relaxation that computes reasonably good lower bounds of the objective, and describe a Tabu Search based on pairings insertion and ejection that builds promising solutions.