A study of joint aggregate production planning : markdown pricing decision making problem under crisp and fuzzy environments

Abstract

The market for perishable products is highly competitive over the world. Markdown pricing is an almost necessary, and effective, tool for increasing profits. This study examines the significance of aligning the markdown pricing policy with aggregate production planning by developing a model, Aggregate Production Planning-Markdown Pricing Model (APPMP), in both deterministic and uncertain environments. It is developed by integrating the Markdown Pricing model (MP) into the Aggregate Production Planning model (APP). APPMP is considered as a joint pricing-production decision making model that offers significant potential for improving enterprise and supply chain performance. APPMP is essentially an integer nonlinear programming model that makes pricing decisions, including the magnitude and time of markdown(s), and operational decisions, e.g. inventory, outsourcing, etc., simultaneously. Numerical examples show that profits in results of APPMP are definitely higher than individual pricing and production models. Further, we develop three scenarios to explore more implications for the adoption of APPMP model under different situations: a) multiple markdown opportunities; b) unconstrained subcontracting capacity; c) negative markdown impact. Besides, we conduct an extensive sensitivity analysis to identify specific favorable factors or areas in which coordination between marketing and production departments can effectively improve efficiency in terms of expected performance, under a deterministic environment. We also employ an interactive fuzzy programming theory to incorporate real world uncertainty into the crisp APPMP model in order to develop a fuzzy version of APPMP, Fuzzy APPMP (or FAPPMP), in which demand and some cost coefficients are fuzzy. In order to solve FAPPMP, we adopt a general methodology to transform FAPPMP into a crisp multi-objective nonlinear programming model for obtaining a compromise solution. Fuzzy APPMP model is capable of appropriately dealing with uncertainty and helps avoid the risk of running a wrong crisp APPMP model. In addition, discussions on practical applications of the APPMP model are provided, and we summarize the study in the final section. The significance of this research can be summarized into following aspects. (i) This study extends the general discrete-time pricing-production model by expanding components of pricing and production respectively. (ii) Joint markdown pricing-aggregate production model is more suitable for perishable products. We have developed a demand function to describe the characteristics of perishable products’ demand pattern. (iii) Few papers have described ways of quantitatively measuring the degree to which markdowns affect quantity of sales. This study proposes a distinct method to estimate the markdown impact. (iv) This dissertation first applies the fuzzy programming model to study coordination problem to address vague and imprecise information in the system. Key words: Markdown Policy Aggregate Production Planning Perishable Products Joint Pricing-Production System Interactive Fuzzy Programming