Search

A Branch-and-Cut algorithm using Benders decomposition method is proposed.The algorithm is applied in case of integer subproblem.Local and Global Cuts are used to warm start the master problem in each node.The validity of the cuts is mathematically proved.A case study tests the efficiency of the algorithm. The application of Benders decomposition method to a problem might result in a subproblem including integer variables. In this case, it is not able to apply the classical Benders algorithm. In this study we present a Branch-and-Cut algorithm, which introduces the notion of Local Cuts as well as Global Cuts. The integrality constraints of the subproblem are relaxed and the relaxed problem is solved in a branch-and-bound framework, where in each node, the Benders algorithm is applied between the master problem and the relaxed subproblem. Benders cuts generated in a node of the branch-and bound tree are proved to be valid for all its descendants, but they are not necessarily valid for the non-descendant nodes. These cuts, referred to as local cuts, can be used to warm start the master problem of each descendant node, thus leading to better initial bounds. Furthermore, a novel way is presented for defining the local cuts in a general form. This general form is in fact a function of the subproblems variables and enables us to reuse the generated (local) cuts in the whole tree by updating some values of the function. The performance of the proposed algorithm is tested on the classical Capacitated Fixed Charge Multiple Knapsack Problem (CFCMKP).

In this paper, we are concerned with the split equality problem of finding an element in the zero point set of the sum of two monotone operators and in the common fixed point set of a finite family of quasi-nonexpansive set-valued mappings. Strong convergence theorems are established under suitable condition in an infinite dimensional Hilbert spaces. Some applications of the main results are also provided.

In this paper, a new variable partitioning strategy in Benders decomposition method is applied that enables us to deal with a wide class of mixed-integer nonlinear programming problems including fixed-charge multicommodity network design (FMND) problems under congestion effects. It is proved that the proposed technique for an FMND problem leads to a simple branch-and-bound algorithm such that each node of the branching tree includes a single conic quadratic representable problem consisting of only continuous (flow) variables. Preliminary numerical results are reported.

This paper deals with multi-commodity flow problem with fractional objective function. The optimality conditions and the duality concepts of this problem are given. For this aim, the fractional linear programming formulation of this problem is considered and the weak duality, the strong direct duality and the weak complementary slackness theorems are proved applying the traditional duality theory of linear programming problems which is different from same results in Chadha and Chadha (2007) [1]. In addition, a strong (strict) complementary slackness theorem is derived which is firstly presented based on the best of our knowledge. These theorems are transformed in order to find the new reduced costs for fractional multi-commodity flow problem. These parameters can be used to construct some algorithms for considered multi-commodity flow problem in a direct manner. Throughout the paper, the boundedness of the primal feasible set is reduced to a weaker assumption about solvability of primal problem which is another contribution of this paper. Finally, a real world application of the fractional multi-commodity flow problem is presented.