Green Profit Maximization Through Joint Pricing and Production Planning of New and Remanufactured Products

Author(s):  
Minjung Kwak ◽  
Katherine Koritz ◽  
Harrison M. Kim

To achieve “green profit” in their business, manufacturers who produce both new and remanufactured products must optimize their pricing and production decisions simultaneously. They must determine the buy-back price and take-back quantity of end-of-life products as well as the selling prices and production quantities of new and remanufactured products. With an aim to assist in optimal pricing and production planning, this paper presents a mixed-integer programming model that optimizes the three prices (of buyback, new and remanufactured products) and the corresponding production plan simultaneously. The model considers the two conflicting objectives of maximizing economic profitability and maximizing environmental impact saving. The model helps address potential barriers to remanufacturing, which include limited economic, and/or environmental sustainability of remanufacturing, imbalance between the supply of end-of-life products and the market demand for remanufactured products, and cannibalization of the sales of new products. The developed model is illustrated with an example of engine water pump.

2021 ◽  
Vol 54 (2) ◽  
pp. 273-281
Author(s):  
Güzin Tirkeş ◽  
Neşe Çelebi ◽  
Cenk Güray

A great deal of research has been undertaken in recent years related to facility capacity expansion and production planning problems under deterministic and stochastic constraints in the literature. However, only a small portion of this work directly addresses the issues faced by the food and beverage industry, especially in small-sized enterprises. In this study, a Mixed-Integer Linear Programming model (MILP) is developed for production planning and scheduling decisions for a small-size company producing syrup and jam products. The main constraint is that the multiple syrup and jam production lines in the model share the same limited-capacity module designed for inventory planning. To this end, the present model offers an efficient solution for executing a multi-product, multi-period production line by finding the most satisfactory strategy to match the right product with the useable capacity leading to profit maximization. The present approach is capable of coping with varying demands by offering a detailed costing procedure and implementing an effective inventory model.


2020 ◽  
Vol 6 (1) ◽  
Author(s):  
S Mohd Baki ◽  
Jack Kie Cheng

Production planning is often challenging for small medium enterprises (SMEs) company. Most of the SMEs are having difficulty in determining the optimal level of the production output which can affect their business performance. Product mix optimization is one of the main key for production planning. Many company have used linear programming model in determining the optimal combination of various products that need to be produced in order to maximize profit. Thus, this study aims for profit maximization of a SME company in Malaysia by using linear programming model. The purposes of this study are to identify the current process in the production line and to formulate a linear programming model that would suggest a viable product mix to ensure optimum profitability for the company. ABC Sdn Bhd is selected as a case study company for product mix profit maximization study. Some conclusive observations have been drawn and recommendations have been suggested. This study will provide the company and other companies, particularly in Malaysia, an exposure of linear programming method in making decisions to determine the maximum profit for different product mix.


2021 ◽  
Vol 9 ◽  
pp. 64-73
Author(s):  
S. Mohd Baki ◽  
J.K. Cheng

Production planning is often challenging for small medium enterprises (SMEs) company. Most of the SMEs are having difficulty in determining the optimal level of the production output which can affect their business performance. Product mix optimization is one of the main key for production planning. Many company have used linear programming model in determining the optimal combination of various products that need to be produced in order to maximize profit. Thus, this study aims for profit maximization of a SME company in Malaysia by using linear programming model. The purposes of this study are to identify the current process in the production line and to formulate a linear programming model that would suggest a viable product mix to ensure optimum profitability for the company. ABC Sdn Bhd is selected as a case study company for product mix profit maximization study. Some conclusive observations have been drawn and recommendations have been suggested. This study will provide the company and other companies, particularly in Malaysia, an exposure of linear programming method in making decisions to determine the maximum profit for different product mix.


Author(s):  
Eduardo A. Pina ◽  
Miguel A. Lozano ◽  
Luis M. Serra

The increasing world energy demand as a result of society development brings forth a growing environmental concern. The use of high-efficiency alternative systems is becoming progressively more interesting due to economic reasons and regional incentives. The issue of finding the best configuration that minimizes total annual cost is not enough anymore, as the environmental concern has become one of the objectives in the synthesis of energy systems. The minimization of costs is often contradictory to the minimization of environmental impact. Multi-objective optimization tackles the conflicting objectives issue by providing a set of trade-off solutions, or Pareto solutions, that can be examined by the decision maker in order to choose the best configuration for the given scenario. The present work proposes a mixed integer linear programming model for the synthesis of a trigeneration system that must attend the electricity, heat, and cooling demands of a multifamily building complex in Zaragoza, Spain. The objective functions to be minimized are the overall annual costs and the overall annual CO2 emissions, considering investment, maintenance and operation costs. As a first approach, the single-objective configurations for each objective function are evaluated. Then, the Pareto frontier is obtained for the minimization of total annual costs and total annual CO2 emissions, allowing to obtain the best trade-off configuration, which brings results close to the optimal single objectives. It is worth mentioning that the treatment of the energy prices was simplified in order to keep on the same level of detail as energy CO2 emissions, which are given only on an annual basis. On the other hand, the optimization model developed can be further complicated in order to consider more complex situations.


2017 ◽  
Vol 17 (3) ◽  
pp. 133-138
Author(s):  
A. Stawowy ◽  
J. Duda

Abstract In the paper, we present a coordinated production planning and scheduling problem for three major shops in a typical alloy casting foundry, i.e. a melting shop, molding shop with automatic line and a core shop. The castings, prepared from different metal, have different weight and different number of cores. Although core preparation does not required as strict coordination with molding plan as metal preparation in furnaces, some cores may have limited shelf life, depending on the material used, or at least it is usually not the best organizational practice to prepare them long in advance. Core shop have limited capacity, so the cores for castings that require multiple cores should be prepared earlier. We present a mixed integer programming model for the coordinated production planning and scheduling problem of the shops. Then we propose a simple Lagrangian relaxation heuristic and evolutionary based heuristic to solve the coordinated problem. The applicability of the proposed solution in industrial practice is verified on large instances of the problem with the data simulating actual production parameters in one of the medium size foundry.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xin Zou ◽  
Guangchuan Wu ◽  
Qian Zhang

PurposeRepetitive projects play an important role in the construction industry. A crucial point in scheduling this type of project lies in enabling timely movement of crews from unit to unit so as to minimize the adverse effect of work interruptions on both time and cost. This paper aims to examine a repetitive scheduling problem with work continuity constraints, involving a tradeoff among project duration, work interruptions and total project cost (TPC). To enhance flexibility and practicability, multi-crew execution is considered and the logic relation between units is allowed to be changed arbitrarily. That is, soft logic is considered.Design/methodology/approachThis paper proposes a multi-objective mixed-integer linear programming model with the capability of yielding the optimal tradeoff among three conflicting objectives. An efficient version of the e-constraint algorithm is customized to solve the model. This model is validated based on two case studies involving a small-scale and a practical-scale project, and the influence of using soft logic on project duration and total cost is analyzed via computational experiments.FindingsUsing soft logic provides more flexibility in minimizing project duration, work interruptions and TPC, especial for non-typical projects with a high percentage of non-typical activities.Research limitations/implicationsThe main limitation of the proposed model fails to consider the learning-forgetting phenomenon, which provides space for future research.Practical implicationsThis study assists practitioners in determining the “most preferred” schedule once additional information is provided.Originality/valueThis paper presents a new soft logic-based mathematical programming model to schedule repetitive projects with the goal of optimizing three conflicting objectives simultaneously.


2015 ◽  
Vol 2015 ◽  
pp. 1-20 ◽  
Author(s):  
Shan Lu ◽  
Hongye Su ◽  
Lian Xiao ◽  
Li Zhu

This paper tackles the challenges for a production planning problem with linguistic preference on the objectives in an uncertain multiproduct multistage manufacturing environment. The uncertain sources are modelled by fuzzy sets and involve those induced by both the epistemic factors of process and external factors from customers and suppliers. A fuzzy multiobjective mixed integer programming model with different objective priorities is proposed to address the problem which attempts to simultaneously minimize the relevant operations cost and maximize the average safety stock holding level and the average service level. The epistemic and external uncertainty is simultaneously considered and formulated as flexible constraints. By defining the priority levels, a two-phase fuzzy optimization approach is used to manage the preference extent and convert the original model into an auxiliary crisp one. Then a novel interactive solution approach is proposed to solve this problem. An industrial case originating from a steel rolling plant is applied to implement the proposed approach. The numerical results demonstrate the efficiency and feasibility to handle the linguistic preference and provide a compromised solution in an uncertain environment.


Author(s):  
S Mohd Baki ◽  
Jack Kie Cheng

Production planning is often challenging for small medium enterprises (SMEs) company. Most of the SMEs are having difficulty in determining the optimal level of the production output which can affect their business performance. Product mix optimization is one of the main key for production planning. Many company have used linear programming model in determining the optimal combination of various products that need to be produced in order to maximize profit. Thus, this study aims for profit maximization of a SME company in Malaysia by using linear programming model. The purposes of this study are to identify the current process in the production line and to formulate a linear programming model that would suggest a viable product mix to ensure optimum profitability for the company. ABC Sdn Bhd is selected as a case study company for product mix profit maximization study. Some conclusive observations have been drawn and recommendations have been suggested. This study will provide the company and other companies, particularly in Malaysia, an exposure of linear programming method in making decisions to determine the maximum profit for different product mix.


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