Super efficiency in vector optimization with nearly convexlike set-valued maps

In this paper, we establish a scalarization theorem and a Lagrange multiplier theorem for super efficiency in vector optimization problem involving nearly convexlike set-valued maps. A dual is proposed and duality results are obtained in terms of super efficient solutions. A new type of saddle point, called super saddle point, of an appropriate set-valued Lagrangian map is introduced and is used to characterize super efficiency.     

New facets for the two-stage uncapacitated facility location polytope

The two-stage uncapacitated facility location problem is considered. This problem involves a system providing a choice of depots and plants, each with an associated location cost, and a set of demand points which must be supplied, in such a way that the total cost is minimized. The formulations used until now to approach the problem were symmetric in plants and depots. In this paper the asymmetry inherent to the problem is taken into account to enforce the formulation which can be seen like a set packing problem and new facet defining inequalities for the convex hull of the feasible solutions are obtained. A computational study is carried out which illustrates the interest of the new facets. A new family of facets recently developed, termed lifted fans, is tested with success.     

The Singular Limit Problem to the Extended Cahn–Hillard Equation

A mathematical model with a small parameter, which describes the hardening process of the binary tin–lead alloy, is investigated on the basis of nonlinear asymptotic analysis. A singular limit problem, namely an extended Stefan problem in the case of short relaxation time in the phase transformation zone, is derived. We prove the existence of an asymptotic solution with any accuracy on the time interval where the solution to the singular limit problem exists. The phase-separation interface is determined uniquely by three leading approximations. We also show that the stability of the separation interface depends on the so-called dissipation condition obtained for the solutions of the interface problem. Nonsymmetry of the surface tension tensor leads to a situation where the limit values of concentration distributions are in dependence on the geometry of the interface. This provokes the dispersion of the interface problem solutions on the part of the interface that not is tangent to the main crystallographic axis.     

Time discretisation of monotone nonlinear evolution problems by the discontinuous Galerkin method

A class of discontinuous Galerkin methods is studied for the time discretisation of the initial-value problem for a nonlinear first-order evolution equation that is governed by a monotone, coercive, and hemicontinuous operator. The numerical solution is shown to converge towards the weak solution of the original problem. Furthermore, well-posedness of the time-discrete problem as well as a priori error estimates for sufficiently smooth exact solutions are studied.     

Robust H∞ control for linear Markovian jump systems with unknown nonlinearities

This paper studies the problem of stochastic stability and disturbance attenuation for a class of linear continuous-time uncertain systems with Markovian jumping parameters. The uncertainties are assumed to be nonlinear and state, control and external disturbance dependent. A sufficient condition is provided to solve the above problem. An H_∞ controller is designed such that the resulting closed-loop system is stochastically stable and has a disturbance attenuation γ for all admissible uncertainties. It is shown that the control law is in terms of the solutions of a set of coupled Riccati inequalities. A numerical example is included to demonstrate the potential of the proposed technique.     

Optimization of Measure-Driven Hybrid Systems

We study an optimal control problem for a state-dependent impulse system described by a measure differential equation. A specific time reparameterization technique is developed to reduce the impulsive control problem to the one with bounded controls. Necessary conditions of optimality are obtained by interpreting the Maximum Principle in the reduced problem. An impulsive control improvement scheme is outlined. The results of numeric simulation are presented.     

A stochastic bi-objective location model for strategic reverse logistics

In this paper we propose a comprehensive model for reverse logistics planning where many real-world features are considered such as the existence of several facility echelons, multiple commodities, choice of technology and stochasticity associated with transportation costs and waste generation. Moreover, we adopt a bi-objective model for the problem. First, the cost for building and operating the network is to be minimized. Second, the obnoxious effect caused by the reverse network facilities is also to be minimized. A two-stage stochastic bi-objective mixed-integer programming formulation is proposed, in which the strategic decisions are considered in the first stage and the tactical/operational decisions in the second one. A set of different scenarios is considered, and the extensive form of the deterministic equivalent problem is presented. This model is tested with a case study based on some data from the Spanish province of Cordoba. Nondominated solutions are obtained by combining the two different objectives and by using a general solver.     

Block Difference Schemes of High Order for Stiff Linear Differential-Algebraic Equations

Computational Mathematics and Mathematical Physics - The initial value problem for stiff linear differential-algebraic equations is considered. A block variant of multistep difference...     

Reconstructing (0,1)-matrices from projections using integer programming

We study the problem of reconstructing (0,1)-matrices based on projections along a small number of directions. This discrete inverse problem is generally hard to solve for more than 3 projection directions. Building on previous work by the authors, we give a problem formulation with the objective of finding matrices with the maximal number of neighboring ones. A solution approach based on variable splitting and the use of subgradient optimization is given. Further, computational results are given for some structured instances. Optimal solutions are found for instances with up to 10,000 binary variables.     

Optimal Impulsive Control Problem with Application to Human Immunodeficiency Virus Treatment

This paper describes an optimal control problem involving a nonlinear impulsive control system, together with a nonlinear objective function and nonlinear control and state constraints. Both the magnitude of the impulses as well as the instants at which the impulses are applied can be regarded as decision variables. A computational method is described for solving the problem. To illustrate the usefulness of our method for real-life applications, we solve a Human Immunodeficiency Virus (HIV) treatment problem. The numerical results obtained clearly illustrate the efficiency of our method.     

A Parameter-Uniform B-Spline Collocation Method for Singularly Perturbed Semilinear Reaction-Diffusion Problems

We consider a Dirichlet boundary value problem for a class of singularly perturbed semilinear reaction-diffusion equations. A  B-spline collocation method on a piecewise-uniform Shishkin mesh is developed to solve such problems numerically. The convergence analysis is given and the method is shown to be almost second-order convergent, uniformly with respect to the perturbation parameter ε in the maximum norm. Numerical results are presented to validate the theoretical results.     

Inverse subsemigroups and classes of finite aperiodic semigroups

We prove a number of results related to finite semigroups and their inverse subsemigroups, including the following. (1) A finite semigroup is aperiodic if and only if it is a homomorphic image of a finite semigroup whose inverse subsemigroups are semilattices. (2) A finite inverse semigroup can be represented by order-preserving mappings on a chain if and only if it is a semilattice. Finally, we introduce the concept of pseudo-small quasivariety of finite semigroups, generalizing the concept of small variety.     

A biased random-key genetic algorithm with forward-backward improvement for the resource constrained project scheduling problem

This paper presents a biased random-key genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. Active schedules are constructed using a priority-rule heuristic in which the priorities of the activities are defined by the genetic algorithm. A forward-backward improvement procedure is applied to all solutions. The chromosomes supplied by the genetic algorithm are adjusted to reflect the solutions obtained by the improvement procedure. The heuristic is tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.     

Switching Time Optimization for Bang-Bang and Singular Controls

Optimal control problems with the control variable appearing linearly are studied. A method for optimization with respect to the switching times of controls containing both bang-bang and singular arcs is presented. This method is based on the transformation of the control problem into a finite-dimensional optimization problem. Therein, first and second-order optimality conditions are thoroughly discussed. Explicit representations of first and second-order variational derivatives of the state trajectory with respect to the switching times are given. These formulas are used to prove that the second-order sufficient conditions can be verified on the basis of only first-order variational derivatives of the state trajectory. The effectiveness of the proposed method is tested with two numerical examples.     

Necessary Optimality Conditions for Some Control Problems of Elliptic Equations with Venttsel Boundary Conditions

In this paper we derive a necessary optimality condition for a local optimal solution of some control problems. These optimal control problems are governed by a semi-linear Vettsel boundary value problem of a linear elliptic equation. The control is applied to the state equation via the boundary and a functional of the control together with the solution of the state equation under such a control will be minimized. A constraint on the solution of the state equation is also considered.     

Simultaneous siting and sizing of distribution centers on a plane

The benefits of simultaneous consideration of siting and sizing of distribution centers have been well acknowledged in supply chain design. Most formulations assume that the potential DC sites are known and the decision on location is to select sites from the finite potential DC sites. However, the quality of this discrete version problem depends on the selection of potential DC sites. In this paper we present a planar version of the problem, which assumes that there is no a priori knowledge of DC sites and DCs can be located anywhere in the plane. The goal of the problem is to simultaneously find locations and sizing of DC sites. The solution of the planar problem provides a lower bound for the discrete problem. The objective of the problem is to minimize the total of inbound and outbound transportation costs and distribution center construction costs—which include its fixed charge cost and concave sizing cost. The problem is initially formulated as a nonlinear programming model. We then reformulate it as a set covering problem after establishing certain key properties. A greedy drop heuristic and a column generation heuristic are developed to solve the problem. Computational experiments are provided.     

A composite algorithm for multiprocessor scheduling

A composite algorithm is developed for the classical problem of scheduling independent jobs on identical parallel machines with the objective of minimizing the makespan. The algorithm at first obtains a family of initial partial solutions and combines these partial solutions until a feasible solution is generated. Then local search procedures are used for improving the solution. The effectiveness of this approach is evaluated through extensive computational comparisons with recent improvement heuristics for different classes of benchmark instances.     

Stationarity Conditions and Their Reformulations for Mathematical Programs with Vertical Complementarity Constraints

We consider the mathematical program with vertical complementarity constraints. We show that the min-max-min problems and the problems with max-min constraints can be reformulated as the above problem. As a complement of the work of Scheel and Scholtes in 2000, we derive the Mordukhovich-type stationarity conditions for the considered problem. We further reformulate various popular stationarity systems as nonlinear equations with simple constraints. A modified Levenberg–Marquardt method is employed to solve these constrained equations.     

On the Solution of Generalized Multiplicative Extremum Problems

The paper addresses the problem of maximizing a sum of products of positive and concave real-valued functions over a convex feasible set. A reformulation based on the image of the feasible set through the vector-valued function which describes the problem, combined with an adequate application of convex analysis results, lead to an equivalent indefinite quadratic extremum problem with infinitely many linear constraints. Special properties of this later problem allow to solve it by an efficient relaxation algorithm. Some numerical tests illustrate the approach proposed.     

On the convergence of the Weiszfeld algorithm for continuous single facility location–allocation problems

A general family of single facility continuous location–allocation problems is introduced, which includes the decreasingly weighted ordered median problem, the single facility Weber problem with supply surplus, and Weber problems with alternative fast transportation network. We show in this paper that the extension of the well known Weiszfeld iterative decrease method for solving the corresponding location problems with fixed allocation yields an always convergent scheme for the location allocation problems. In a generic way, from each starting point, the limit point will be a locally minimal solution, whereas for each possible exceptional situation, a possible solution is indicated. Some computational results are presented, comparing this method with an alternating location–allocation approach. The research of the second author was partially supported by the grant of the Algerian Ministry of High Education 001BIS/PNE/ENSEIGNANTS/BELGIQUE.