In this paper we propose an approach for solving problems of optimal resource capacity allocation to a collection of stochastic dynamic competitors. In particular, we introduce the knapsack problem for perishable items, which concerns the optimal dynamic allocation of a limited knapsack to a collection of perishable or non-perishable items. We formulate the problem in the framework of Markov de...

We study the Knapsack Problem with Conflict Graph (KPCG), an extension of the 0-1 Knapsack Problem, in which a conflict graph describing incompatibilities between items is given. The goal of the KPCG is to select the maximum profit set of compatible items while satisfying the knapsack capacity constraint. We present a Branch-and-Bound approach to derive optimal solutions to the KPCG in short co...

Knapsack problems are important NP-Complete combinatorial optimization problems. Although nearly all the classical instances can be solved in pseudo-polynomial time nowadays, yet there are a variety of test problems which are hard to solve for the existing algorithms. In this paper we propose a new approach based upon binary particle swarm optimization algorithm (BPSO) to find solutions of thes...

— Chosen-ciphertext security, which guarantees confidentiality of encrypted messages even in the presence of a decryption oracle, has become the de facto notion of security for public-key encryption under active attack. In this manuscript, for the first time, we propose a new approach for constructing post-quantum cryptosystems secure against adaptive chosen ciphertext attack (CCA2-secure) in t...

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]...

An employee transporting problem is described and a set partitioning model is developed. An investigation of the model leads to a knapsack problem as a surrogate problem. Finding a partition corresponding to the knapsack problem provides a solution to the problem. An exact algorithm is proposed to obtain a partition (subset-vehicle combination) corresponding to the knapsack solution. It require...

The mean eld theory (MFT) approach to knapsack problems is extended to multiple knapsacks and generalized assignment problems with Potts mean eld equations governing the dynamics. Numerical tests against \state of the art" conventional algorithms shows good performance for the mean eld approach. The inherently parallelism of the MFT equations makes them suitable for direct implementations in mi...

A knapsack problem is to select a set of items that maximizes the total profit selected while keeping weight no less than capacity knapsack. As generalized form with multiple knapsacks, multi-knapsack (MKP) disjointed for each To solve MKP, we propose deep reinforcement learning (DRL) based approach, which takes as input available capacities profits and weights items, normalized unselected dete...