We propose a class of quadratic optimization problems whose exact optimal objective values can be computed by their completely positive cone programming relaxations. The objective function can be any quadratic form. The constraints of each problem are described in terms of quadratic forms with no linear terms, and all constraints are homogeneous equalities, except one inhomogeneous equality whe...

This paper studies the constrained multi-location assortment optimization problem under joint delivery by drone and human courier. To maximize revenue of retailer, product last-mile methods are configured simultaneously. handle with assortment, a mixed multinomial logit model is established to depict customer purchase behavior. We also take into account load capacity drones distance limit couri...

Modeling and solving real world problems is one of the most important issues in optimization problems. In this paper, we present an approach to solve Fuzzy Interval Flexible Linear Programming (FIFLP) problems that simultaneously have the interval ambiguity in the matrix of coefficients .In the first step, using the interval problem solving techniques; we transform the fuzzy interval flexible p...

Every real-life optimization problem with uncertainty and hesitation can not be a single objective, consequently, class of multiobjective linear problems (MOLOP) appears in the literature. Further, experts assign values uncertain parameters, expert’s opinions about parameters are conflicting nature. There concerning methods based on fuzzy sets, or their other versions available literature that ...

nowadays, different methods are used to solve optimization problems which ,one of the newest is bco method that are inspired by the nature and derived from the social life of bees of these methods can be noted that bco is derived from the social life of bees. we use in this paper fuzzy logic for bee‟s decision stage. at the end, we solve two different problem that have already been solved by es...

We consider linear optimization problems over the cone of copositive matrices. Such conic optimization problems, called copositive programs, arise from the reformulation of a wide variety of difficult optimization problems. We propose a hierarchy of increasingly better outer polyhedral approximations to the copositive cone. We establish that the sequence of approximations is exact in the limit....

In this paper we consider l0 regularized convex cone programming problems. In particular, we first propose an iterative hard thresholding (IHT) method and its variant for solving l0 regularized box constrained convex programming. We show that the sequence generated by these methods converges to a local minimizer. Also, we establish the iteration complexity of the IHT method for finding an -loca...

Many optimization problems gain from being interpreted and solved in either primal or dual form. For a user with a particular application, one of these forms is usually much more natural to use, but this is not always the most efficient one. This paper presents an implementation in the optimization modelling tool YALMIP that allows the user to define conic optimization problems in a preferred f...