An evolutionary economic perspective on technical change and adjustment in cane harvesting systems in the Australian sugar industry

Australian sugar-producing regions have differed in terms of the extent and rate of incorporation of new technology into harvesting systems. The Mackay sugar industry has lagged behind most other sugar-producing regions in this regard. The reasons for this are addressed by invoking an evolutionary economics perspective. The development of harvesting systems, and the role of technology in shaping them, is mapped and interpreted using the concept of path dependency. Key events in the evolution of harvesting systems are identified, which show how the past has shaped the regional development of harvesting systems. From an evolutionary economics perspective, the outcomes observed are the end result of a specific history.

Expansion-based algorithms for finding single pair shortest path on surface

Finding single pair shortest paths on surface is a fundamental problem in various domains, like Geographic Information Systems (GIS) 3D applications, robotic path planning system, and surface nearest neighbor query in spatial database, etc. Currently, to solve the problem, existing algorithms must traverse the entire polyhedral surface. With the rapid advance in areas like Global Positioning System (CPS), Computer Aided Design (CAD) systems and laser range scanner, surface models axe becoming more and more complex. It is not uncommon that a surface model contains millions of polygons. The single pair shortest path problem is getting harder and harder to solve. Based on the observation that the single pair shortest path is in the locality, we propose in this paper efficient methods by excluding part of the surface model without considering them in the search process. Three novel expansion-based algorithms are proposed, namely, Naive algorithm, Rectangle-based Algorithm and Ellipse-based Algorithm. Each algorithm uses a two-step approach to find the shortest path. (1) compute an initial local path. (2) use the value of this initial path to select a search region, in which the global shortest path exists. The search process terminates once the global optimum criteria are satisfied. By reducing the searching region, the performance is improved dramatically in most cases.