Optimising resource portfolio planning for capital-intensive industries under process-technology progress

Abstract

This paper addresses the problem of resource portfolio planning of firms in high-tech, capital-intensive manufacturing industries. In light of the strategic importance of resource portfolio planning in these industries, we offer an alternative approach to modelling capacity planning and allocation problems that improves the deficiencies of prior models in dealing with three salient features of these industries, i.e. fast technological obsolescence, volatile market demand, and high capital expenditure. This paper first discusses the characteristics of resource portfolio planning problems including capacity adjustment and allocation. Next, we propose a new mathematical programming formulation that simultaneously optimises capacity planning and task assignment. For solution efficiency, a constraint-satisfied genetic algorithm (CSGA) is developed to solve the proposed mathematical programming problem on a real-time basis. The proposed modelling scheme is employed in the context of a semiconductor testing facility. Experimental results show that our approach can solve the resource portfolio planning problem more efficiently than a conventional optimisation solver. The overall contribution is an analytical tool that can be employed by decision makers responding to the dynamic technological progress and new product introduction at the strategic resource planning level.

Entrepreneurial Resources, Complementary Assets, and Platform Sustainability

“…As shown in the table above, we conducted the identification of the entrepreneurial resources of the case company CZB using a large amount of second-hand data and part of the interview data, and the following findings were made: First, high-tech, capital-intensive industries, such as internet energy platforms, feature high capital expenditure [65]. CZB also has the characteristic of a fast financing speed.…”

Tactical production planning for physical and financial flows of supply chain in a multi-site context

“…The authors showed the strength of their solution procedure based on Benders' Decomposition which significantly reduce the solution time and is promising for an application of a real world scenario. Yang et al (2009) investigated simultaneously task assignment, resource allocation and equipment acquisition/disposal decision within a scenario based-resource portfolio model. Thomas & Bollapragada (2010) developed an analytical decision tool based on a capacity planning model to estimate product costs and demands in order to maximize the NPV of profit for General Electric.…”

Single-site strategic capacity planning considering renewal, maintenance, inventory, taxes and cash flow management

“…Some examples of models that jointly address these decisions are proposed by Wang et al (2007a), Yang et al (2009), Zhang et al (2012 and Lim et al (2013), among others.…”

“…Traditional capacity planning models implicitly assume that all investment is financed by equity. Other models (found in Wang et al, 2007b;Yang et al, 2009, among others) investigated the capacity expansion problem under budget constraints.…”

“…Rajagopalan & Soteriou (1994), Rajagopalan (1998), Wang et al (2007a) and Yang et al (2009) present deterministic models that include the possibility of capacity expansion and reduction.…”