The optimal location of production areas and processing plants in the New Zealand tomato processing industry
Abstract
The location and the spatial relationships between production and processing shift through time due to changes in such factors as production methods, processing, transportation and market structure. This study is concerned with such relationships in the tomato processing industry in New Zealand.
In the past, the regional distribution of production and processing tomatoes has been determined by the historical location and capacity of the processing facilities. However, the merger of smaller companies into larger concerns has caused the some re-location of production into fewer and more specialised regions. More recently there have been changes in production techniques which are expected to further modify the spatial distribution of production and processing within this industry.
The changes in production techniques have sufficiently altered the growing requirements for outdoor tomatoes such that a number of new production regions now have the potential to establish a tomato processing operation.
The objective of this study is the investigation of the optimal location of production areas and processing plants for the rational expansion of the New Zealand tomato processing industry, given various levels of demand.
The perishability and the relatively short distances over which raw tomatoes can be transported and still retain good quality mean that processing p1ants have traditionally been located in production regions. The study investigates the feasibility of decentralised processing operations where initial processing plants, located in production regions, produce an intermediate (pulped) product for shipment to finishing and canning plants located at marketing or trans-shipment points.
The Logan and King model using the stammer-modified solution procedure is used to derive the least cost solution for the location of production areas and the size, type and location of processing plants.
The Logan and King model is a normative optimising approach which produces a single minimum cost solution. However, cost minimisation alone is often too naive an objective for a decision-maker and thus heuristic methods are employed to provide low cost or near optimal solutions. These solutions provide a range of alternative spatial patterns for production and processing that can be fitted to the decision-makers specific needs. The sensitivity of the optimal solution to changes in major cost factors is also investigated.
