Amin Saghaeeian, Reza Ramezanian,
Volume 28, Issue 4 (11-2017)
Abstract
This study considers pricing, production and transportation decisions in a Stackelberg game between three-stage, multi-product, multi-source and single-period supply chains called leader and follower. These chains consist of; manufacturers, distribution centers (DCs) and retailers. Competition type is horizontal and SC vs. SC. The retailers in two chains try to maximize their profit through pricing of products in different markets and regarding the transportation and production costs. A bi-level nonlinear programming model is formulated in order to represent the Stackelberg game. Pricing decisions are based on discrimination pricing rules, where we can put different prices in different markets. After that the model is reduced to single-level nonlinear programming model by replacing Karush-Kuhn-Tucker conditions for the lower level (follower) problem. Finally, a numerical example is solved in order to analyze the sensitivity of effective parameters on price and profit.
Hadi Mokhtari, Aliakbar Hasani, Ali Fallahi,
Volume 32, Issue 2 (6-2021)
Abstract
One of the basic assumptions of classical production-inventory models is that all products are of perfect quality. However, in real manufacturing situations, the production of defective items is inevitable, and a fraction of the items produced may be naturally imperfect. In fact, items may be damaged due to production and/or transportation conditions in the manufacturing process. On the other hand, some reworkable items exist among imperfect items that can be made perfect by additional processing. In addition, the classical production-inventory models assume that there is only one product in the system and that there is an unlimited amount of resources. However, in many practical situations, several products are produced and there are some constraints related to various factors such as machine capacity, storage space, available budget, number of allowable setups, etc. Therefore, we propose new constrained production-inventory models for multiple products where the manufacturing process is defective and produces a fraction of imperfect items. A percentage of defective items can be reworked, and these products go through the rework process to become perfect and return to the consumption cycle. The goal is to determine economic production quantities to minimize the total cost of the system. The analytical solutions are each derived separately by Lagrangian relaxation method, and a numerical example is presented to illustrate and discuss the procedure. A sensitivity analysis is performed to investigate how the variation in the inputs of the models affects the total cost of the inventory system. Finally, some research directions for future works are discussed.
