Open Access
Adeinat, Hamza
Graduate Program:
Industrial Engineering
Doctor of Philosophy
Document Type:
Date of Defense:
June 15, 2016
Committee Members:
  • Dissertation, Dissertation Advisor
  • Price Sensitive Demand
  • Supplier Selection
  • Serial Inventory System
  • Heuristic Algorithm.
The purpose of this research is to develop supply chain inventory models that simultaneously coordinate supplier selection and pricing decisions for a range of retailing situations. The selection of appropriate suppliers plays an important role in improving companies’ purchasing performance. Many researchers and firms have studied the supplier selection problem without taking into account the price-sensitive nature of the demand for certain products. A product’s selling price has a significant impact not only on a company’s ability to attract consumers, but also on its strategic decisions on matters such as supplier selection that are taken at the upstream stages of the supply chain. In this dissertation, we start with the development of a new mathematical model for the supplier selection problem that refines and generalizes some of the existing models in the literature. We propose a mixed integer nonlinear programming (MINLP) model to find the optimal inventory replenishment policy for a particular type of raw material in a supply chain defined by a single manufacturer and multiple suppliers. Each supplier offers an all-unit quantity discount as an incentive mechanism. Multiple orders can be submitted to the selected suppliers within a repeating order cycle. We initially assume the demand rate to be constant. The model provides the optimal number of orders and corresponding order quantities for the selected suppliers such that the replenishment and inventory cost per time unit is minimized under suppliers’ capacity and quality constraints. Then, we extend the model to simultaneously find the optimal selling price and replenishment policy for a particular type of product in a supply chain defined by a single retailer and multiple potential suppliers. Hence, we replace the manufacturer with a retailer subject to a demand rate considered to be dependent on the selling price. We propose an MINLP model to find the optimal order frequency and corresponding order quantity allocated to each selected supplier, and the optimal demand rate and selling price such that the profit per time unit is maximized taking into consideration suppliers’ limitation on capacity and quality. In addition, we provide sufficient conditions under which there exists an optimal solution where the retailer only orders from one supplier. We also apply the Karush–Kuhn–Tucker conditions to investigate the impact of the supplier’s capacity on the optimal sourcing strategy. The results show that there may exist a range of capacity values for the dominating supplier, where the retailer’s optimal sourcing strategy is to order from multiple suppliers without fully utilizing the dominating supplier’s capacity. Next, we study the integrated pricing and supplier selection problem in a two-stage supply chain that comprises a manufacturer stage followed by a retailer stage, both controlled by a single decision-maker. The manufacturer can procure the required raw material from a list of potential suppliers, each of which has constraints in regard to capacity and quality. In this model, the manufacturer periodically replenishes the retailer’s inventory, the demand for which is proving to be price-sensitive. We propose an MINLP model designed to determine the optimal replenishment policy for the raw material, the optimal amount of inventory replenished at each stage, and the optimal final product’s selling price at which the profit per time unit is maximized. Additionally, we provide upper and lower bounds for the optimal selling price and for the manufacturer’s lot size multiplicative factor, which result in a tight feasible search space. Next, we propose an MINLP model to extend the prior model by considering a serial supply chain controlled by a decision-maker responsible for maximizing the profit per time unit by determining the following: the optimal amount of raw material to order from the selected suppliers, the optimal amount of product to transfer between consecutive stages in order to avoid any inventory shortage, and the optimal final product’s selling price. Coordinating all these decisions simultaneously is a topic that has been neglected in literature. In addition, our model requires the order quantity received from each selected supplier to be an integer multiple of the order quantity delivered to the following stage, which means that a different multiplicative factor can be assigned to each supplier. This coordination mechanism shows an improvement in the objective function compared to those of existing models that assign the same multiplicative factor to each selected supplier. Moreover, we develop a heuristic algorithm that generates near-optimal solutions. A numerical example is presented to illustrate the proposed model and the heuristic algorithm.