Genetic algorithm for the continuous location-routing problem

This paper focuses on the continuous location-routing problem that comprises of the location of multiple depots from a given region and determining the routes of vehicles assigned to these depots. The objective of the problem is to design the delivery system of depots and routes so that the total cost is minimal. The standard location-routing problem considers a finite number of possible locations. The continuous location-routing problem allows location to infinite number of locations in a given region and makes the problem much more complex. We present a genetic algorithm that tackles both location and routing subproblems simultaneously.Web of Science29318717

Optimal fault-tolerant placement of relay nodes in a mission critical wireless network

The operations of many critical infrastructures (e.g., airports) heavily depend on proper functioning of the radio communication network supporting operations. As a result, such a communication network is indeed a mission-critical communication network that needs adequate protection from external electromagnetic interferences. This is usually done through radiogoniometers. Basically, by using at least three suitably deployed radiogoniometers and a gateway gathering information from them, sources of electromagnetic emissions that are not supposed to be present in the monitored area can be localised. Typically, relay nodes are used to connect radiogoniometers to the gateway. As a result, some degree of fault-tolerance for the network of relay nodes is essential in order to offer a reliable monitoring. On the other hand, deployment of relay nodes is typically quite expensive. As a result, we have two conflicting requirements: minimise costs while guaranteeing a given fault-tolerance. In this paper address the problem of computing a deployment for relay nodes that minimises the relay node network cost while at the same time guaranteeing proper working of the network even when some of the relay nodes (up to a given maximum number) become faulty (fault-tolerance). We show that the above problem can be formulated as a Mixed Integer Linear Programming (MILP) as well as a Pseudo-Boolean Satisfiability (PB-SAT) optimisation problem and present experimental results com- paring the two approaches on realistic scenarios

Real valued negative selection for anomaly detection in wireless ad hoc networks

Wireless ad hoc network is one of the network technologies that have gained lots of attention from computer scientists for the future telecommunication applications. However it has inherits the major vulnerabilities from its ancestor (i.e., the fixed wired networks) but cannot inherit all the conventional intrusion detection capabilities due to its features and characteristics. Wireless ad hoc network has the potential to become the de facto standard for future wireless networking because of its open medium and dynamic features. Non-infrastructure network such as wireless ad hoc networks are expected to become an important part of 4G architecture in the future. In this paper, we study the use of an Artificial Immune System (AIS) as anomaly detector in a wireless ad hoc network. The main goal of our research is to build a system that can learn and detect new and unknown attacks. To achieve our goal, we studied how the real-valued negative selection algorithm can be applied in wireless ad hoc network network and finally we proposed the enhancements to real-valued negative selection algorithm for anomaly detection in wireless ad hoc network

Swarm-Based Spatial Sorting

Purpose: To present an algorithm for spatially sorting objects into an annular structure. Design/Methodology/Approach: A swarm-based model that requires only stochastic agent behaviour coupled with a pheromone-inspired "attraction-repulsion" mechanism. Findings: The algorithm consistently generates high-quality annular structures, and is particularly powerful in situations where the initial configuration of objects is similar to those observed in nature. Research limitations/implications: Experimental evidence supports previous theoretical arguments about the nature and mechanism of spatial sorting by insects. Practical implications: The algorithm may find applications in distributed robotics. Originality/value: The model offers a powerful minimal algorithmic framework, and also sheds further light on the nature of attraction-repulsion algorithms and underlying natural processes.Comment: Accepted by the Int. J. Intelligent Computing and Cybernetic

A multidirectional modified Physarum solver for discrete decision making

In this paper, a bio-inspired algorithm able to incrementally grow decision graphs in multiple directions is presented. The heuristic draws inspiration from the behaviour of the slime mould Physarum Polycephalum. In its main vegetative state, the plasmodium, this large single-celled amoeboid organism extends and optimizes a net of veins looking for food. The algorithm is here used to solve classical problems in operations research (symmetric Traveling Salesman and Vehicle Routing Problems). Simulations on selected test cases demonstrate that a multidirectional modied Physarum solver performs better than a unidirectional one. The ability to evaluate decisions from multiple directions enhances the performance of the solver in the construction and selection of optimal decision sequences