Online knapsack problem is considered, where items arrive in a sequential fashion that have two attributes; value and weight. Each arriving item has to be accepted or rejected on its arrival irrevocably. The objective is to maximize the sum of the value of the accepted items such that the sum of their weights is below a budget/capacity. Conventionally a hard budget/capacity constraint is consid...

We establish the optimal input signaling and the capacity of MIMO channels under per-antenna power constraint. While admitting a linear eigenbeam structure, the optimal input is no longer diagonalizable by the channel right singular vectors as with sum power constraint. We formulate the capacity optimization as an SDP problem and solve in closed-form the optimal input covariance as a function o...

We describe a constraint programming approach to establish the coal carrying capacity of a large (2,670km) rail network in northeastern Australia. Computing the capacity of such a network is necessary to inform infrastructure planning and investment decisions but creating a useful model of rail operations is challenging. Analytic approaches exist but they are not very accurate. Simulation metho...

In the first case s* remains equal to 2, in the next three cases s* is equal to 1, and in the last three cases s* becomes 0. MO= 3 1 0 MI= 0 1 3 .

A practical communication channel often suffers from constraints on input other than the average power, such as the peak power constraint. In order to compare achievable rates with different constellations as well as the channel capacity under such constraints, it is crucial to take these constraints into consideration properly. In this paper, we propose a direct approach to compare the achieva...

Scheduling can be formalized as a constraint satisfaction problem (CSP). Within this framework activities in a plan are interconnected via temporal relation constraints a la Allen, thereby defining a temporal constraint graph (TCG). Additionally there are capacity constraints restricting the use of each resource to only one activity at a time. Together these constraints form a temporallcapacity...

The amplitude-constrained capacity of a scalar Gaussian channel is shown to be achieved by a unique discrete random variable taking on a finite number of values. Necessary and sufficient conditions for the distribution of this random variable are obtained. These conditions permit determination of the random variable and capacity as a function of the constraint value. The capacity of the same Ga...

We provide a counterexample to Cover’s conjecture that the feedback capacity CFB of an additive Gaussian noise channel under power constraint P be no greater than the nonfeedback capacity C of the same channel under power constraint 2P , i.e., CFB(P ) C(2P ). Index Terms|Additive Gaussian noise channels, channel capacity, conjecture, counterexample, feedback.

in this paper, we develop a capacitated location-covering model considering interval values for demand and service parameters. we also consider flexibility on distance standard for covering demand nodes by the servers. we use the satisfaction degree to represent the constraint of service capacity. the proposed model belongs to the class of mixed integer programming models. our model can be redu...