Coordinated Supplier Selection, Inventory Replenishment, and Pricing Decisions in Supply Chain Management
Open Access
- Author:
- Duan, Lisha
- Graduate Program:
- Industrial Engineering
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- September 28, 2018
- Committee Members:
- José A. Ventura, Dissertation Advisor/Co-Advisor
José A. Ventura, Committee Chair/Co-Chair
Eunhye Song, Committee Member
Huanan Zhang, Committee Member
Saurabh Bansal, Outside Member - Keywords:
- Supply chain management
Supplier selection
Integrated inventory planning
Length of time period
Price-sensitive demand
Logit demand function
Decentralized supply chain
Game theory - Abstract:
- Given the popularity of inventory models with supplier selection, this research aims to develop mathematical models for the integrated procurement, inventory planning, and pricing problems in the presence of multiple capacitated suppliers and price-sensitive demand in supply chains, simultaneously determining the selling pricing and inventory policy under a variety of supply contracts. We starts with the development of an operational planning model in a demand-driven serial supply chain with multiple capacitated suppliers. Taking into account delivery time and order frequency, the suppliers offer a novel price break scheme, which is beneficial to both the supplier and the buyer. A mixed-integer linear programming (MILP) formulation is developed to address this dynamic supplier selection and inventory management model aiming at minimizing the overall incurred cost across the entire supply chain with capacity constraints in production, inventory, and transportation. Then, the length of the time period is considered as a variable. A new MILP formulation is derived when each period of the model is split into multiple sub-periods, and under certain conditions, it is proved that the optimal solution and objective value of the original model form a feasible solution and an upper bound for the derived model. Sufficient evidence demonstrates that the length of the time period has a significant influence on supplier selection, lot sizing allocation, and inventory planning decisions. Then, we investigate joint decision making of supplier selection, pricing, and inventory lot-sizing in a two-stage supply chain, where suppliers feature certain capacity and quality levels and the retailer faces a price-sensitive demand, characterized by the logit function. Multiple orders can be placed to potential suppliers within a repeating order cycle. The retailer purchases the items satisfying a lower bound on the average quality level to meet customer demand. In this context, we develop a mathematical model to find an optimal solution for the selling price and inventory replenishment policy, including the set of selected suppliers, order frequency, and order quantity. We further derive a lower bound on the optimal retail price and based on a two-stage piecewise linear approximation (PLA) technique, we develop heuristic algorithms to yield near-optimal solutions to the proposed model. Besides, we provide sufficient justification for the selection of the logit demand function as well as a comparison with other demand functions. A numerical study further suggests the importance of using a precise demand curve to select the set of suppliers, coordinate inventory, and accurately optimize the profit function. Next, we extend the joint pricing, supplier selection and inventory replenishment model to a serial supply chain with multiple stages in a centralized control scenario. Within this supply chain, the first stage faces a supplier selection decision for a particular product that experiences a price-sensitive demand. The buying stage needs to decide which suppliers to choose and how to allocate orders, determining the optimal inventory policy for all stages and the retail price to offer to end customers, while maximizing the total profit of the supply chain. The problem is formulated as a mixed integer nonlinear programming (MINLP) model and a heuristic algorithm is proposed to overcome the complexity of the model. Then, we analyze a special case that considers only one uncapacitated supplier and one buyer. An efficient heuristic is developed and computational experiments are carried out to examine the performance of the proposed heuristics. In addition, we provide a series of numerical examples to illustrate our results and analyze the impact of the parameters within a sensitivity analysis. Finally, we study a pricing and purchasing problem in a two-stage supply chain with one supplier and one retailer, where the retailer faces the price-sensitive demand and the supplier coordinates the supply chain with controllable delivery deviation. Both the retailer’s demand and the supplier’s lead time are stochastic. A risk sharing supply contract is adopted and the supplier compensates the retailer by paying a portion of penalties for early/late delivery. In this direction, we establish a model with a game-theoretic approach to achieve supply chain coordination, simultaneously determining the retailer’s selling price, order quantity, and order date as well as the supplier’s lead time variance. Besides, the models with respect to the constant delivery deviation are also developed and analyzed. Finally, a numerical example is presented and sensitivity analysis regarding the pricing and penalty parameters provide in-depth managerial insights for decision makers.