A mathematical programming approach to deal with the global configuration of resource constraints is presented. A specialized parametric programming algorithm to obtain the pareto set for the biobjective problem that appears to deal with the global configuration for 0-1-Integer Linear Programing problems is presented and implemented. Computational results for Multiconstrained Knapsack problems ...

In this study, biobjective mixed-integer linear programming problems are considered and a search-andremove (SR) algorithm is presented. At each stage of the algorithm, Pareto outcomes are searched with the dichotomic search algorithm and these outcomes are excluded from the objective space with the help of Tabu constraints. The algorithm is also enhanced with lower and upper bounds, which are u...

we consider biobjective shortest path problems in networks with fuzzy arc lengths. considering the available studies for single objective shortest path problems in fuzzy networks, using a distance function for comparison of fuzzy numbers, we propose three approaches for solving the biobjective prob- lems. the rst and second approaches are extensions of the labeling method to solve the sing...

We consider biobjective shortest path problems in networks with fuzzy arc lengths. Considering the available studies for single objective shortest path problems in fuzzy networks, using a distance function for comparison of fuzzy numbers, we propose three approaches for solving the biobjective prob- lems. The rst and second approaches are extensions of the labeling method to solve the sing...

We present a generic branch-and-bound algorithm for finding all the Pareto solutions of biobjective mixed-integer linear program. The main contributions are new algorithms obtaining dual bounds at node, checking node fathoming, presolve, and duality gap measurement. Our is predominantly decision space search method because branching performed on variables, akin to single objective problems, alt...

This paper is devoted to a study of the impact of using bound sets in biobjective optimization. This notion, introduced by Villareal and Karwan [19], has been independently revisited by Ehrgott and Gandibleux [9], as well as by Sourd and Spanjaard [17]. The idea behind it is very general, and can therefore be adapted to a wide range of biobjective combinatorial problem. We focus here on the bio...

The conventional linear programming model requires the parameters to be known as constants. In the real world, however, the parameters are seldom known exactly and have to be estimated. Interval programming is one of the tools to tackle uncertainty in mathematical programming models. In this paper, it will be presented the linear programming problems with interval numbers as coefficients and va...