Network Topology and Time Criticality Effects in the Modularised Fleet Mix Problem

In this paper, we explore the interplay between network topology and time criticality in a military logistics system. A general goal of this work (and previous work) is to evaluate land transportation requirements or, more specifically, how to design appropriate fleets of military general service vehicles that are tasked with the supply and re-supply of military units dispersed in an area of operation. The particular focus of this paper is to gain a better understanding of how the logistics environment changes when current Army vehicles with fixed transport characteristics are replaced by a new generation of modularised vehicles that can be configured task-specifically. The experimental work is conducted within a well developed strategic planning simulation environment which includes a scenario generation engine for automatically sampling supply and re-supply missions and a multi-objective meta-heuristic search algorithm (i.e. Evolutionary Algorithm) for solving the particular scheduling and routing problems. The results presented in this paper allow for a better understanding of how (and under what conditions) a modularised vehicle fleet can provide advantages over the currently implemented system

An Empirical Study of Cohesion and Coupling: Balancing Optimisation and Disruption

Search based software engineering has been extensively applied to the problem of finding improved modular structures that maximise cohesion and minimise coupling. However, there has, hitherto, been no longitudinal study of developers’ implementations, over a series of sequential releases. Moreover, results validating whether developers respect the fitness functions are scarce, and the potentially disruptive effect of search-based remodularisation is usually overlooked. We present an empirical study of 233 sequential releases of 10 different systems; the largest empirical study reported in the literature so far, and the first longitudinal study. Our results provide evidence that developers do, indeed, respect the fitness functions used to optimise cohesion/coupling (they are statistically significantly better than arbitrary choices with p << 0.01), yet they also leave considerable room for further improvement (cohesion/coupling can be improved by 25% on average). However, we also report that optimising the structure is highly disruptive (on average more than 57% of the structure must change), while our results reveal that developers tend to avoid such disruption. Therefore, we introduce and evaluate a multi-objective evolutionary approach that minimises disruption while maximising cohesion/coupling improvement. This allows developers to balance reticence to disrupt existing modular structure, against their competing need to improve cohesion and coupling. The multi-objective approach is able to find modular structures that improve the cohesion of developers’ implementations by 22.52%, while causing an acceptably low level of disruption (within that already tolerated by developers)

Optimal modularity: A demonstration of the evolutionary advantage of modular architectures

Modularity is an important concept in evolutionary theorizing but lack of a consistent definition renders study difficult. Using the generalised NK-model of fitness landscapes, we differentiate modularity from decomposability. Modular and decomposable systems are both composed of subsystems but in the former these subsystems are connected via interface standards while in the latter subsystems are completely isolated. We derive the optimal level of modularity, which minimises the time required to globally optimise a system, both for the case of two-layered systems and for the general case of multi-layered hierarchical systems containing modules within modules. This derivation supports the hypothesis of modularity as a mechanism to increase the speed of evolution. Our formal definition clarifies the concept of modularity and provides a framework and an analytical baseline for further research.Modularity, Decomposability, Near-decomposability, Complexity, NK-model, Search, hierarchy

Effectively incorporating expert knowledge in automated software remodularisation

Remodularising the components of a software system is challenging: sound design principles (e.g., coupling and cohesion) need to be balanced against developer intuition of which entities conceptually belong together. Despite this, automated approaches to remodularisation tend to ignore domain knowledge, leading to results that can be nonsensical to developers. Nevertheless, suppling such knowledge is a potentially burdensome task to perform manually. A lot information may need to be specified, particularly for large systems. Addressing these concerns, we propose the SUMO (SUpervised reMOdularisation) approach. SUMO is a technique that aims to leverage a small subset of domain knowledge about a system to produce a remodularisation that will be acceptable to a developer. With SUMO, developers refine a modularisation by iteratively supplying corrections. These corrections constrain the type of remodularisation eventually required, enabling SUMO to dramatically reduce the solution space. This in turn reduces the amount of feedback the developer needs to supply. We perform a comprehensive systematic evaluation using 100 real world subject systems. Our results show that SUMO guarantees convergence on a target remodularisation with a tractable amount of user interaction

The impact of modularisation strategies on small modular reactor cost

Small Modular Reactors (SMRs) based on established light-water technology have gained a lot of attention from the nuclear industry; however, the potential that SMRs have to reduce the cost of nuclear construction has been under-studied. Modularisation is a cost reducing mechanism where a SMR power plant is subdivided into smaller units, or modules. These modules can be produced offsite in a controlled environment, potentially offering cost reductions that offset their apparently higher capital costs. This paper will investigate the effects modularisation and standardisation might have on SMR capital costs. Modularisation and standardisation not only reduce direct and indirect costs, respectively, but also enable activation of other cost-reducing mechanisms, such as shifting construction work from site to a factory, transferring learning between tasks, and achieving economies of multiples. It will show that constructing a SMR using the same methods as current large reactors is not economically feasible and will demonstrate how modularisation reduces SMR capital costs. The primary constraints on module size are imposed by weight and height transport limitations, linking reactor size to ease of modularisation. This leads to an analysis of which SMR components and structures should be targeted for modularisation in order to achieve optimal cost benefits

The Life-Cycle Income Analysis Model (LIAM): a study of a flexible dynamic microsimulation modelling computing framework

This paper describes a flexible computing framework designed to create a dynamic microsimulation model, the Life-cycle Income Analysis Model (LIAM). The principle computing characteristics include the degree of modularisation, parameterisation, generalisation and robustness. The paper describes the decisions taken with regard to type of dynamic model used. The LIAM framework has been used to create a number of different microsimulation models, including an Irish dynamic cohort model, a spatial dynamic microsimulation model for Ireland, an indirect tax and consumption model for EU15 as part of EUROMOD and a prototype EU dynamic population microsimulation model for 5 EU countries. Particular consideration is given to issues of parameterisation, alignment and computational efficiency.flexible; modular; dynamic; alignment; parameterisation; computational efficiency

Designing active objects in DEGAS

This report discusses application design for active databases, in particular for the active object-based database programming language DEGAS. In DEGAS one modularisation principle, the object, is applied to all elements of the application, including rules. We discuss a design process consisting of four phases, corresponding with the four kinds of capabilities in a DEGAS object, attributes, methods, rules, lifecycles. The elements of this design process are similar to those found in a design methodology such as OMT. To illustrate the design process we use the example of workflow management. In addition, it shows that the application of one modularisation to all elements of an active database leads to a clear modularisation of the workflow application, Furthermore, this modularisation facilitates all important workflow evolutions

The Effect of Supply Chain Configuration on Small Modular Reactor Economics

This thesis examines the opportunity presented by small modular reactors (SMRs) to bring down the cost of nuclear power. The economies of scale that have traditionally driven nuclear vendors to design larger reactors can be overcome for small reactors by the combination of standardisation of design, modularisation of the build process, and progressive reduction in production cost through learning. By employing the most comprehensive nuclear plant construction cost data available, in conjunction with established cost estimating methods, a model was devised to estimate the capital costs and levelized electricity cost of a SMR, based on conventional light water reactor technology. Key elements of supply chain configuration were parameterised in the model, enabling the investigation of its effect on SMR economics. Credible SMR supply chain configurations were hypothesised, by applying procurement decision models to industry data and nuclear sector specific constraints. These configurations were evaluated using the model against a range of programme conditions. Beyond single programme supply chain design, the challenges posed by global production and deployment were considered, such as the segmentation of market demand, variations in labour costs, and the implications of regulatory barriers and localisation for SMR cost reduction methods. The costs of first developing a SMR programme were also estimated. It was established that in order for SMRs to become cost competitive with large nuclear plants, a sizeable programme of at least 10 GW of standard units is needed to achieve sufficient production volume and production rate. The preferred SMR size is in the region of 250 MWe, to achieve a balance between economies of scale and learning. Progress needs to be made in harmonising global technical standards and safety regulation to make the product-like reactor concept feasible. Moreover, a committed supply chain of collaborative enterprise partners, rather than competing transactional suppliers, is required to realise the necessary learning cost reduction.Funded by EPSRC through the ICO CDT in Nuclear Energ