the vehicle routing problem with backhauls (vrpb) as an extension of the classical vehicle routing prob-lem (vrp) attempts to define a set of routes which services both linehaul customers whom product are to be delivered and backhaul customers whom goods need to be collected. a primary objective for the problem usually is minimizing the total distribution cost. most real-life problems have othe...

this paper uses the l1−norm and the concept of the non-dominated vector, topropose a method to find a well-dispersed subset of non-dominated (wdsnd) vectorsof a multi-objective mixed integer linear programming (momilp) problem.the proposed method generalizes the proposed approach by tohidi and razavyan[tohidi g., s. razavyan (2014), determining a well-dispersed subset of non-dominatedvectors of...

We study the structure of dual optimization problems associated with linear constraints, bounds on the variables, and separable cost. We show how the separability of the dual cost function is related to the sparsity structure of the linear equations. As a result, techniques for ordering sparse matrices based on nested dissection or graph partitioning can be used to decompose a dual optimization...

Many real-world optimization models comprise nonconvex and nonlinear as well as nonsmooth functions leading to very hard classes of optimization models. In this article a new interior-point method for the special but practically relevant class of optimization problems with locatable and separable nonsmooth aspects is presented. After motivating and formalizing the problems under consideration, ...

The pupose of this paper is modeling of Partial Digest Problem (PDP) as a mathematical programming problem. In this paper we present a new viewpoint of PDP. We formulate the PDP as a continuous optimization problem and develope a method to solve this problem. Finally we constract a linear programming model for the problem with an additional constraint. This later model can be solved by the simp...

We study a multiperiod portfolio selection problem in which a single period meanstandard-deviation criterion is used to construct a separable multiperiod selection criterion. Using this criterion, we obtain a closed form optimal strategy which depends on selection schemes of investor’s risk preference. As a consequence, we develop a multiperiod portfolio selection scheme. In doing so, we adapt ...

In this paper, we develop a parameterized proximal point algorithm (PPPA) for solving a class of separable convex programming problems subject to linear and convex constraints. The proposed algorithm is provable to be globally convergent with a worst-case O(1/t) convergence rate, where t denotes the iteration number. By properly choosing the algorithm parameters, numerical experiments on solvin...

We consider the problem of minimizing a convex separable logarithmic function over a region defined by a convex inequality constraint or linear equality constraint, and twosided bounds on the variables (box constraints). Such problems are interesting from both theoretical and practical point of view because they arise in somemathematical programming problems as well as in various practical prob...

This correspondence describes an approach to reducing the computational cost of document image decoding by viewing it as a heuristic search problem. The kernel of the approach is a modi ed dynamic programming (DP) algorithm, called the iterated complete path (ICP) algorithm, that is intended for use with separable source models. A set of heuristic functions are presented for decoding formatted ...

We describe a primal-dual interior point algorithm for a class of convex separable programming problems subject to linear constraints. Each iteration updates a penalty parameter and finds a Newton step associated with the Karush-Kuhn-Tucker system of equations which characterizes a solution of the logarithmic barrier function problem for that parameter. It is shown that the duality gap is reduc...