Leveraging Wireless Broadband to Improve Police Land Mobile Radio Programming: Estimating the Resource Impact

Despite rapid growth in criminological studies of police technology, examinations of police land mobile radios are absent in the literature. This is troubling given the central role mobile radios serve in police operations and their significant management costs. The present study seeks to fill this gap by introducing the functionality of wireless broadband radio programming. Current practice requires a police officer to physically drive to a radio programming location to manage their mobile radio. Wireless programming remedies this burdensome reality, thereby saving officer time and cost. Geospatial analyses are used to estimate distance saved associated with wireless programming. We then conduct a number of calculations to determine time and cost savings related to the observed differences between existing and wireless radio programming within the context of the North Carolina State Highway Patrol. Results suggest wireless radio programming can save significant personnel and financial resources. Implications are discussed

Optimising economic, environmental, and social objectives: a goal-programming approach in the food sector

The business-decision environment is increasingly complicated by the emergence of competing economic, environmental, and social goals, a notion typified by the current pressures of global economic instability and climate-change targets. Trade-offs are often unclear and contributions by different actors and stakeholders in the supply chain may be unequal but, due to the interdependencies between businesses and stakeholders in relation to total environmental or social impact, a whole chain, simultaneous, and strategic approach is required. After a review of relevant literature and the identification of knowledge gaps, the author introduces and illustrates the use of goal programming as a technique that could facilitate this approach and uses real case evidence for alternative food supply chain strategies, at local, regional, and national levels. It is shown that the method can simplify a complex simultaneous decision situation into a useful and constructive decision and planning framework. Results show how a priori beliefs may be challenged and how operational and resource efficiency could be improved through the use of such a model, which enables a broad stakeholder appreciation and the opportunity to explore and test new environmental or social challenges

Stochastic equilibrium models for generation capacity expansion

Capacity expansion models in the power sector were among the first applications of operations research to the industry. The models lost some of their appeal at the inception of restructuring even though they still offer a lot of possibilities and are in many respect irreplaceable provided they are adapted to the new environment. We introduce stochastic equilibrium versions of these models that we believe provide a relevant context for looking at the current very risky market where the power industry invests and operates. We then take up different questions raised by the new environment. Some are due to developments of the industry like demand side management: an optimization framework has difficulties accommodating them but the more general equilibrium paradigm offers additional possibilities. We then look at the insertion of risk related investment practices that developed with the new environment and may not be easy to accommodate in an optimization context. Specifically we consider the use of plant specific discount rates that we derive by including stochastic discount rates in the equilibrium model. Linear discount factors only price systematic risk. We therefore complete the discussion by inserting different risk functions (for different agents) in order to account for additional unpriced idiosyncratic risk in investments. These different models can be cast in a single mathematical representation but they do not have the same mathematical properties. We illustrate the impact of these phenomena on a small but realistic example.capacity adequacy, risk functions, stochastic equilibrium models, stochastic discount factors

Survey on Combinatorial Register Allocation and Instruction Scheduling

Register allocation (mapping variables to processor registers or memory) and instruction scheduling (reordering instructions to increase instruction-level parallelism) are essential tasks for generating efficient assembly code in a compiler. In the last three decades, combinatorial optimization has emerged as an alternative to traditional, heuristic algorithms for these two tasks. Combinatorial optimization approaches can deliver optimal solutions according to a model, can precisely capture trade-offs between conflicting decisions, and are more flexible at the expense of increased compilation time. This paper provides an exhaustive literature review and a classification of combinatorial optimization approaches to register allocation and instruction scheduling, with a focus on the techniques that are most applied in this context: integer programming, constraint programming, partitioned Boolean quadratic programming, and enumeration. Researchers in compilers and combinatorial optimization can benefit from identifying developments, trends, and challenges in the area; compiler practitioners may discern opportunities and grasp the potential benefit of applying combinatorial optimization