A data warehouse is a repository of integrated information available for querying and analysis needed for Business Intelligence. Data warehouses store and conceptualize data in the form of multidimensional model and is represented in the form of data cube or cuboid. In order to analyze the business intelligence related issues analysis is started from the base cuboid (which represents a fact table) and all the possible situations of business queries are depicted by generating all the possible combinations of cuboids which corresponds to lattice structure and is known as lattice of cuboids. A lattice is a large structure as it consists of 2n cuboids where n is the numbers of dimensions participating in the fact table. In the lattice structure a cuboid could be accessed through multiple paths originating from base cuboid. Computation of the best path from these multiple paths is a research challenge involving less storage space and computation time. Survey work reveals that the existing methodologies consider the cardinalities (numbers of distinct values) of the dimensions to generate minimum number of intermediate cubes to reach a given target cube. In this paper a methodology is proposed which considers the size of each dimension along with its cardinality to design a Heuristic based algorithm for formal analysis, leading towards detection of an optimal path for any two given pair of cuboids at different levels. Experimental results on real life data set are given to prove the enhanced space and time complexities of the proposed algorithm over existing methodologies. Copyright 2018 ISCA, CATA