A Primal-Dual Infeasible-Interior-Point Algorithm for Multiple Objective Linear Programming Problems

A primal-dual infeasible interior point algorithm for multiple objective linear programming (MOLP) problems was presented. In contrast to the current MOLP algorithm. moving through the interior of polytope but not confining the iterates within the feasible region in our proposed algorithm result in a solution approach that is quite different and less sensitive to problem size, so providing the potential to dramatically improve the practical computation effectiveness.

Optimality and Duality on Fractional Multi-objective Programming Under Semilocal E-convexity

In this paper, some necessary and sufficient optimality conditions are obtained for a fractional multiple objective programming involving semilocal E-convex and related functions. Also, some dual results are established under this kind of generalized convex functions. Our results generalize the ones obtained by Preda[J Math Anal Appl, 288（2003） 365-382].

OPTIMALITY CONDITIONS AND DUALITY RESULTS FOR NONSMOOTH VECTOR OPTIMIZATION PROBLEMS WITH THE MULTIPLE INTERVAL-VALUED OBJECTIVE FUNCTION

In this paper, both Fritz John and Karush-Kuhn-Tucker necessary optimality conditions are established for a （weakly） LU-efficient solution in the considered nonsmooth multiobjective programming problem with the multiple interval-objective function. Further, the sufficient optimality conditions for a （weakly） LU-efficient solution and several duality results in Mond-Weir sense are proved under assumptions that the functions constituting the considered nondifferentiable multiobjective programming problem with the multiple interval- objective function are convex.

A Compromise Approach to Lexicographic Optimal Solution in Multiple Objective Programming

In this paper we use a compromise approach to identify a lexicographic optimal solution of a multiple objective programming (MOP) problem. With this solution concept, we first find the maximization of each objection function as the ideal value. Then, we construct a lexicographic order for the compromise (differences) between the ideal values and objective functions. Based on the usually lexicographic optimality structure, we discuss some theoretical properties about our approach and derive a constructing algorithm to compute such a lexicographic optimal solution.

Inter-cell downlink co-channel interference management through cognitive sensing in heterogeneous network for LTE-A

Heterogeneous network for long term evolution advanced（LTE-A） creates severe interference.It is an urgent task to overcome the interference in macro cellular with low-power base stations（BSs）,such as relay,pico,and femto called subnet nodes.In this paper,the cognitive interference model in interference zone（IZ） of the practical heterogeneous scenario is proposed.Based on investigation of interaction between the macro BS and subnet nodes in this model,the strategy framework of the cognitive critical ratio and power reward factor is set up for interference management aiming to get the maximum net saving power.The study of interference management is transformed into a multiple objective non-linear programming（MONLP） of the maximum saving power for the macro BS and subnet nodes.To facilitate the best compromise solution for both,the MONLP is changed into single objective programming and genetic algorithm（GA） is employed to obtain the global optimum solution.In addition,the practical implementation using the proposed algorithm in heterogeneous network for LTE-A is designed.Finally,numerical evaluation is used to test the applicability of the proposed algorithm,and system level simulation results demonstrate the effectiveness of the proposed interference management scheme.