This paper is concerned with a variation of the multiple knapsack problem (MKP) [5, 6], where we are given a set of n items N = {1, 2, . . . , n} to be packed into m possible knapsacks M = {1, 2, . . . ,m}. As in ordinary MKP, by w j and p j we denote the weight and profit of item j ∈ N respectively, and the capacity of knapsack i ∈ M is ci. However, a fixed cost fi is imposed if we use knapsac...

The stochastic non-linear fractional knapsack problem is a challenging optimization problem with numerous applications, including resource allocation. The goal is to find the most valuable mix of materials that fits within a knapsack of fixed capacity. When the value functions of the involved materials are fully known and differentiable, the most valuable mixture can be found by direct applicat...

where the pairs (I+$, Xi) 2 0 are assumed to be independent draws from a common . . . . . joint distribution Fwx. If we think of the pairs (w,Xi) as the weights and values, respectively, of a collection of n objects, then this problem can be thought of as finding the collection of objects of maximum value which will fit in a “knapsack” with weight capacity 1. Our main result, Theorem 2.4, compu...

The deterministic knapsack problem is a well known and well studied NP-hard combinatorial optimization problem. It consists in filling a knapsack with items out of a given set such that the weight capacity of the knapsack is respected and the total reward maximized. For a review of references on the stochastic knapsack problem, stochastic gradient algorithms and branch-and-bound methods see [4]...

Motivated by a real world application, we study the multiple knapsack problem with assignment restrictions (MKAR): We are given a set of items N = f1; : : : ; ng and a set of knapsacks M = f1; : : : ;mg. Each item j 2 N has a positive real weight wj and each knapsack i 2 M has a positive real capacity ci associated with it. In addition, for each item j 2 N a set Aj M of knapsacks that can hold ...

In this paper, we present a new methodology to adapt any kind of lattice reduction algorithms to deal with the modular knapsack problem. In general, the modular knapsack problem can be solved using a lattice reduction algorithm, when its density is low. The complexity of lattice reduction algorithms to solve those problems is upper-bounded in the function of the lattice dimension and the maximu...