A note on "optimal resource allocation for security in reliability systems"

In a recent paper by Azaiez and Bier [Azaiez, M.N., Bier, V.M., 2007. Optimal resource allocation for security in reliability systems. European Journal of Operational Research 181, 773–786], the problem of determining resource allocation in series-parallel systems (SPSs) is considered. The results for this problem are based on the results for the least-expected cost failure-state diagnosis problem. In this note, it is demonstrated that the results for the least-expected cost failure-state diagnosis problem for SPSs in Azaiez and Bier (2007) are incorrect. In addition relevant results that were not cited in the paper are summarized

An ant colony algorithm for the sequential testing problem under precedence constraints.

We consider the problem of minimum cost sequential testing of a series (parallel) system under precedence constraints that can be modeled as a nonlinear integer program. We develop and implement an ant colony algorithm for the problem. We demonstrate the performance of this algorithm for special type of instances for which the optimal solutions can be found in polynomial time. In addition, we compare the performance of the algorithm with a special branch and bound algorithm for general instances. The ant colony algorithm is shown to be particularly effective for larger instances of the problem

A taxonomy for emergency service station location problem

The emergency service station (ESS) location problem has been widely studied in the literature since 1970s. There has been a growing interest in the subject especially after 1990s. Various models with different objective functions and constraints have been proposed in the academic literature and efficient solution techniques have been developed to provide good solutions in reasonable times. However, there is not any study that systematically classifies different problem types and methodologies to address them. This paper presents a taxonomic framework for the ESS location problem using an operations research perspective. In this framework, we basically consider the type of the emergency, the objective function, constraints, model assumptions, modeling, and solution techniques. We also analyze a variety of papers related to the literature in order to demonstrate the effectiveness of the taxonomy and to get insights for possible research directions

Power allocation and routing for full-duplex multi hop wireless networks under full interference

When traditional half-duplex (HD) radios are employed in indoor wireless mesh networks, such as home networks, interference among mesh nodes is a major impairment, as the end-to-end throughput is to be shared between all transmitting nodes. Full-duplex (FD) relaying can improve the end-to-end throughput, as simultaneous transmissions and receptions, hence simultaneous links are enabled, but FD nodes are subject to self-interference(SI) in addition to inter-node interference, resulting in a more complicated, full interference scenario. In this work, a power allocation solution is proposed along with routing for enabling FD in such multi hop wireless networks subject to full interference. First, an optimization problem is formulated for maximizing the end-to-end throughput of FD relaying on a given, known path, considering the full interference model. A linear programming based solution is devised to obtain the optimal transmit power levels for FD relaying nodes on the path. Then, for joint power allocation and routing in an FD mesh network, Dijkstra’s algorithm is modified by applying the proposed power allocation in the calculation of the path metrics. Via detailed numerical experiments considering different system parameters, such as network size, SI cancellation capability, maximum power level per node, it is shown that the proposed FD relaying with power control based on full interference model outperforms not only HD relaying, but also an existing FD relaying solution based on a single hop interference model. The amount of improvement by FD relaying depends on the system settings. For instance, for low power budget systems, HD throughput can be tripled, while for systems with high power budget, FD relaying achieves 80 percent higher throughput over HD relaying. When power control is combined with routing, the end-to-end throughput performance of the proposed FD routing solution again outperforms the existing solutions. Depending on the power budget, up to two times higher throughput is achieved over FD routing based on single hop interference, and HD routing can be improved by up to five times even for moderate SI cancellation levels. Our results suggest that employing proposed joint power allocation and routing scheme, migration to FD can be beneficial for home wireless mesh networks under full interference, especially for bandwidth-hungry applications, such as video streaming, gaming

Exact and heuristic approaches to detect failures in failed k-out-of-n systems

This paper considers a k-out-of-n system that has just failed. There is an associated cost of testing each component. In addition, we have apriori information regarding the probabilities that a certain set of components is the reason for the failure. The goal is to identify the subset of components that have caused the failure with the minimum expected cost. In this work, we provide exact and approximate policies that detects components’ states in a failed k-out-of-n system. We propose two integer programming (IP) formulations, two novel Markov decision process (MDP) based approaches, and two heuristic algorithms. We show the limitations of exact algorithms and effectiveness of proposed heuristic approaches on a set of randomly generated test instances. Despite longer CPU times, IP formulations are flexible in incorporating further restrictions such as test precedence relationships, if need be. Numerical results illustrate that dynamic programming for the proposed MDP model is the most effective exact method, solving up to 12 components within one hour. The heuristic algorithms’ performances are presented against exact approaches for small to medium sized instances and against a lower bound for larger instances

Minimum power multicasting with delay bound constraints in Ad Hoc wireless networks

In this paper, we design a new heuristic for an important extension of the minimum power multicasting problem in ad hoc wireless networks. Assuming that each transmission takes a fixed amount of time, we impose constraints on the number of hops allowed to reach the destination nodes in the multicasting application. This setting would be applicable in time critical or real time applications, and the relative importance of the nodes may be indicated by these delay bounds. We design a filtered beam search procedure for solving this problem. The performance of our algorithm is demonstrated on numerous test cases by benchmarking it against an optimal algorithm in small problem instances, and against a modified version of the well-known Broadcast Incremental Power (BIP) algorithm 20 for relatively large problems

Testing systems of identical components

We consider the problem of testing sequentially the components of a multi-component reliability system in order to figure out the state of the system via costly tests. In particular, systems with identical components are considered. The notion of lexicographically large binary decision trees is introduced and a heuristic algorithm based on that notion is proposed. The performance of the heuristic algorithm is demonstrated by computational results, for various classes of functions. In particular, in all 200 random cases where the underlying function is a threshold function, the proposed heuristic produces optimal solutions