Multilevel refinement for combinatorial optimisation: boosting metaheuristic performance

The multilevel paradigm as applied to combinatorial optimisation problems is a simple one, which at its most basic involves recursive coarsening to create a hierarchy of approximations to the original problem. An initial solution is found, usually at the coarsest level, and then iteratively refined at each level, coarsest to finest, typically by using some kind of heuristic optimisation algorithm (either a problem-specific local search scheme or a metaheuristic). Solution extension (or projection) operators can transfer the solution from one level to another. As a general solution strategy, the multilevel paradigm has been in use for many years and has been applied to many problem areas (for example multigrid techniques can be viewed as a prime example of the paradigm). Overview papers such as [] attest to its efficacy. However, with the exception of the graph partitioning problem, multilevel techniques have not been widely applied to combinatorial problems and in this chapter we discuss recent developments. In this chapter we survey the use of multilevel combinatorial techniques and consider their ability to boost the performance of (meta)heuristic optimisation algorithms.

An architecture of multiple heterogeneous case-based reasoning employing agent technologies

This paper presents an investigation into applying Case-Based Reasoning to Multiple Heterogeneous Case Bases using agents. The adaptive CBR process and the architecture of the system are presented. A case study is presented to illustrate and evaluate the approach. The process of creating and maintaining the dynamic data structures is discussed. The similarity metrics employed by the system are used to support the process of optimisation of the collaboration between the agents which is based on the use of a blackboard architecture. The blackboard architecture is shown to support the efficient collaboration between the agents to achieve an efficient overall CBR solution, while using case-based reasoning methods to allow the overall system to adapt and “learn” new collaborative strategies for achieving the aims of the overall CBR problem solving process.

REDUCING DIESEL DEPENDENCE IN NUNAVUT: INTEGRATING RENEWABLE ENERGY TECHNOLOGIES THROUGH POLICY ACTIONS

In the last fifty years, Nunavut has developed a deep dependence on diesel for virtually all of its energy needs, including electricity. This dependence has created a number of economic, environmental and health related challenges in the territory, with an estimated 20% of the territory’s annual budget being spent on energy, thereby limiting the Government of Nunavut’s ability to address other essential infrastructure and societal needs, such as education, nutrition and health care and housing. One solution to address this diesel dependency is the use of renewable energy technologies (RETs), such as wind, solar and hydropower. As such, this thesis explores energy alternatives in Nunavut, and through RETScreen renewable energy simulations, found that solar power and wind power are technically viable options for Nunavut communities and a potentially successful means to offset diesel-generated electricity in Nunavut. However, through this analysis it was also discovered that accurate data or renewable resources are often unavailable for most Nunavut communities. Moreover, through qualitative open-ended interviews, the perspectives of Nunavut residents with regards to developing RETs in Nunavut were explored, and it was found that respondents generally supported the use of renewable energy in their communities, while acknowledging that there still remains a knowledge gap among residents regarding renewable energy, stemming from a lack of communication between the communities, government and the utility company. In addition, the perceived challenges, opportunities and gaps that exist with regards to renewable energy policy and program development were discussed with government policy-makers through further interviews, and it was discovered that often government departments work largely independently of each other rather than collaboratively, creating gaps and oversights in renewable energy policy in Nunavut. Combined, the results of this thesis were used to develop a number of recommended policy actions that could be undertaken by the territorial and federal government to support a shift towards renewable energy in order to develop a sustainable and self-sufficient energy plan in Nunavut. They include: gathering accurate renewable resource data in Nunavut; increasing community consultations on the subject of renewable energy; building strong partnerships with universities, colleges and industry; developing a knowledge sharing network; and finally increasing accessibility to renewable energy programs and policies in Nunavut.