Vehicle replacement problem via fuzzy multi-objective integer programming

Abstract

In the literature, there are four main types of mathematical models to optimise the replacement decision. The first type is the mathematical models that use the techniques of operations research (OR), the second type is the mathematical models that use the economic life, the third type is the mathematical models that use the age replacement, and the fourth type is the mathematical models that use the repair limits. The mathematical models that optimise the replacement decision could be classified broadly into scrap and replacement mathematical models. The scrap mathematical models compared the costs or profits of the physical assets during finite or infinite planning horizons and determined the decision that optimises the time or the age. This type of mathematical models does not contribute to improving organisations’ objectives, but it optimises time or age to waste the physical assets out of service (Clapham, 1957, Drinkwater and Hastings, 1967). The replacement mathematical models compared the sequences of decisions during finite horizons and determined the sequence of decisions that maximises the profit or minimises the cost. This type of mathematical models contributes to improving organisations’ objectives. The shortcomings in the mathematical models that optimise the replacement decision are in optimising the replacement decision to achieve a single objective and in neglecting the change in objectives’ coefficients in the future. The multi-objectives optimisation and the fuzzy sets theory are the key methods for treating the shortcomings in the replacement mathematical models. The multi-objective optimisation uses the concept of domination to determine the efficient solution which achieves multi-objectives, and the fuzzy sets theory is equivalent to multivariable sensitivity analysis and determines the objectives’ coefficients range due to uncertainty in the future.

Date of Award	1 Aug 2017
Original language	English
Awarding Institution	The University of Manchester
Supervisor	David Ling (Supervisor) & Richard Kirkham (Supervisor)