Problems of wave interaction with a body with arbitrary shape floating or submerged in water are of immense importance in the literature on the linearized theory of water waves. Wave-free potentials are used to construct solutions to these problems involving bodies with circular geometry, such as a submerged or half-immersed long horizontal circular cylinder (in two dimensions) or sphere (in three dimensions). These are singular solutions of Laplace’s equation satisfying the free surface condition and decaying rapidly away from the point of singularity. Wave-free potentials in two and three dimensions for infinitely deep water as well as water of uniform finite depth with a free surface are known in the literature. The method of constructing wave-free potentials in three dimensions is presented here in a systematic manner, neglecting or taking into account the effect of surface tension at the free surface or for water with an ice cover modelled as a thin elastic plate floating on the water. The forms of the wave motion at the upper surface (free surface or ice-covered surface) related to these wave-free potentials are depicted graphically in a number of figures for all the cases considered.

This work focuses on finding optimal dividend payment and capital injection policies to maximize the present value of the difference between the cumulative dividend payment and the possible capital injections with delays. Starting from the classical Cramér–Lundberg process, using the dynamic programming approach, the value function obeys a quasi-variational inequality. With delays in capital injections, the company will be exposed to the risk of financial ruin during the delay period. In addition, the optimal dividend payment and capital injection strategy should balance the expected cost of the possible capital injections and the time value of the delay period. In this paper, the closed-form solution of the value function and the corresponding optimal policies are obtained. Some limiting cases are also discussed. A numerical example is presented to illustrate properties of the solution. Some economic insights are also given.

It has been known for a long time that the equivariant $2+1$ wave map into the $2$-sphere blows up if the initial data are chosen appropriately. Here, we present numerical evidence for the stability of the blow-up phenomenon under explicit violations of equivariance.

There is much interest within the mathematical biology and statistical physics community in converting stochastic agent-based models for random walkers into a partial differential equation description for the average agent density. Here a collection of noninteracting biased random walkers on a one-dimensional lattice is considered. The usual master equation approach requires that two continuum limits, involving three parameters, namely step length, time step and the random walk bias, approach zero in a specific way. We are interested in the case where the two limits are not consistent. New results are obtained using a Fokker–Planck equation and the results are highly dependent on the simulation update schemes. The theoretical results are confirmed with examples. These findings provide insight into the importance of updating schemes to an accurate macroscopic description of stochastic local movement rules in agent-based models when the lattice spacing represents a physical object such as cell diameter.

A stochastic algorithm for bound-constrained global optimization is described. The method can be applied to objective functions that are nonsmooth or even discontinuous. The algorithm forms a partition on the search region using classification and regression trees (CART), which defines a region where the objective function is relatively low. Further points are drawn directly from the low region before a new partition is formed. Alternating between partition and sampling phases provides an effective method for nonsmooth global optimization. The sequence of iterates generated by the algorithm is shown to converge to an essential global minimizer with probability one under mild conditions. Nonprobabilistic results are also given when random sampling is replaced with points taken from the Halton sequence. Numerical results are presented for both smooth and nonsmooth problems and show that the method is effective and competitive in practice.

A Content Distribution Network (CDN) can be defined as an overlay system that replicatescopies of contents at multiple points of a network, close to the final users, with theobjective of improving data access. CDN technology is widely used for the distribution oflarge-sized contents, like in video streaming. In this paper we address the problem offinding the best server for each customer request in CDNs, in order to minimize theoverall cost. We consider the problem as a transportation problem and a distributedalgorithm is proposed to solve it. The algorithm is composed of two independent phases: adistributed heuristic finds an initial solution that may be later improved by adistributed transportation simplex algorithm. It is compared with the sequential versionof the transportation simplex and with an auction-based distributed algorithm.Computational experiments carried out on a set of instances adapted from the literaturerevealed that our distributed approach has a performance similar or better to itssequential counterpart, in spite of not requiring global information about the contentsrequests. Moreover, the results also showed that the new method outperforms thebased-auction distributed algorithm.

The problem of finding structures with minimum stabbing number has received considerableattention from researchers. Particularly, [10]study the minimum stabbing number of perfect matchings (mspm), spanning trees(msst) and triangulations (mstr) associated to set of points in theplane. The complexity of the mstr remains open whilst the other two are known tobe 𝓝𝓟-hard. This paper presents integer programming(ip) formulations for these three problems, that allowed us to solve them tooptimality through ip branch-and-bound (b&b) or branch-and-cut(b&c) algorithms. Moreover, these models are the basis for the developmentof Lagrangian heuristics. Computational tests were conducted with instances taken from theliterature where the performance of the Lagrangian heuristics were compared with that ofthe exact b&b and b&c algorithms. The results reveal that theLagrangian heuristics yield solutions with minute, and often null, duality gaps forinstances with several hundreds of points in small computation times. To our knowledge,this is the first computational study ever reported in which these three stabbing problemsare considered and where provably optimal solutions are given.

In this study, we consider a scheduling environment with m(m ≥ 1) parallel machines.The set of jobs to schedule is divided into K disjoint subsets. Each subset of jobs isassociated with one agent. The K agents compete to perform their jobs on commonresources. The objective is to find a schedule that minimizes a global objective functionf 0, while maintaining the regularobjective function of each agent, f k, at a level nogreater than a fixed value, εk (fk ∈ {fkmax, ∑fk}, k = 0, ..., K). This problem is a multi-agent schedulingproblem with a global objective function. In this study, we consider the casewith preemption and the case without preemption. If preemption is allowed, we propose apolynomial time algorithm based on a network flow approach for the unrelated parallelmachine case. If preemption is not allowed, we propose some general complexity results anddevelop dynamic programming algorithms.

In this article we study the realistic network topology of Synchronous Digital Hierarchy(SDH) networks. We describe how providers fulfill customer connectivity requirements. Weshow that SDH Network design reduces to the Non-Disjoint m-Ring-Star Problem (NDRSP). Wefirst show that there is no two-index integer formulation for this problem. We thenpresent a natural 3-index formulation for the NDRSP together with some classes of validinequalities that are used as cutting planes in a Branch-and-Cut approach. We propose apolyhedral study of a polytope associated with this formulation. Finally, we present ourBranch-and-Cut algorithm and give some experimental results on both random and realinstances.

In this paper we consider the problem of scheduling, on a two-machine flowshop, a set ofunit-time operations subject to time delays with respect to the makespan. This problem isknown to be \hbox{${\cal NP}$}𝒩𝒫-hard in the strong sense. We propose an algorithm basedon a branch and bound enumeration scheme. This algorithm includes the implementation ofnew lower and upper bound procedures, and dominance rules. A computer simulation tomeasure the performance of the algorithm is provided for a wide range of testproblems.

We study an uncapacitated facility location model where customers are served byfacilities of level one, then each level one facility that is opened must be assigned toan opened facility of level two. We identify a polynomially solvable case, and study somevalid inequalities and facets of the associated polytope.