scholarly journals Modeling and Optimization Sustainable Forest Supply Chain Considering Discount in Transportation System and Supplier Selection under Uncertainty

Forests ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 964
Author(s):  
Komeyl Baghizadeh ◽  
Dominik Zimon ◽  
Luay Jum’a

In recent decades, the forest industry has been growingly expanded due to economic conditions, climate changes, environmental and energy policies, and intense demand changes. Thus, appropriate planning is required to improve this industry. To achieve economic, social and environmental goals, a supply chain network is designed based on a multi-period and multi-product Mixed-Integer Non-Linear Programming (MINLP) model in which the objective is to maximize the profit, minimize detrimental environmental effects, improve social effects, and minimize the number of lost demands. In addition, to improve forest industry planning, strategic and tactical decisions have been implemented throughout the supply chain for all facilities, suppliers and machinery. These decisions significantly help to improve processes and product flows and to meet customers’ needs. In addition, because of the presence of uncertainty in some parameters, the proposed model was formulated and optimized under uncertainty using the hybrid robust possibilistic programming (HRPP-II) approach. The -constraint technique was used to solve the multi-objective model, and the Lagrangian relaxation (LR) method was utilized to solve the model of more complex dimensions. A case study in Northern Iran was conducted to assess the efficiency of the suggested approach. Finally, a sensitivity analysis was performed to determine the impact of important parameters on objective functions. The results of this study show that increasing the working hours of machines instead of increasing their number, increasing the capacity of some facilities instead of establishing new facilities and expanding the transport fleet has a significant impact on achieving predetermined goals.

Forests ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 529
Author(s):  
Francisco Vergara ◽  
Cristian Palma ◽  
John Nelson

In the forest supply chain of the coast of British Columbia, the material flows are directed toward the push production of commodity products. This industry has not adopted lean and agile principles due to unclear economic impacts on the supply chain in changing market conditions. We tested the ability of lean and agile principles to improve performance in the coastal integrated forest industry. Mixed integer programming formulations were subject to over–under production capacity, and over–under demand fulfillment penalties to emulate agile, lean, and hybrid manufacturing environments, when solving the planning problem. Assuming that the coastal integrated forest industry performs as a hybrid environment, the profit results of each manufacturing environment were judged. The results show that, opportunities for profit improvement were 11% for adopting an agile environment when demand was stable with low variation and large batches of production. However, profit improvement was non-existent when the same demand attributes apply but with high variation. The opportunities for profit improvement were 12% when an agile environment or lean environment was adopted when demand was stable with low variation and small batches of production. However, opportunities for profit improvements of 15% existed for adopting an agile environment when demand was unstable with high variation and small batches of production.


2008 ◽  
Vol 2 (2) ◽  
pp. 47-62 ◽  
Author(s):  
Waldemar Kaczmarczyk

This paper presents a computational study to evaluate the impact of coordinating production and distribution planning in a two-level industrial supply chain. Three planning methods are compared. The first emulates the traditional way of planning. The two other coordinate plans of the supplier and of all the buyers according to the Vendor Managed Inventory (VMI) approach. The monolithic method solves a single model describing the entire optimization problem. The sequential method copies the imperfect VMI practice. All three methods are implemented by means of Mixed Integer Programming models. The results presented prove that the right choice of planning method is very important for overall cost of the supply chain. In contrast to the previous research, it turned out that information sharing without full coordination may even lead to increase in the overall cost. For some companies applying the VMI approach, developing exact models and solving them almost optimally may therefore be very important.


2020 ◽  
Vol 27 (4) ◽  
Author(s):  
Yan Feng ◽  
Jean-François Audy

Abstract: Forest industry plays an important role in global economy and has significant influences in our lives and the environment that we live in. With the rapid advancement of digital technologies and industrial transformations towards Industry 4.0, similar trend has been found in the forest industry and especially on its forest procurement side. Forestry 4.0 has been proposed as research initiatives in recent years. However, publications have largely focused on the digital technologies. This article is aimed at presenting a framework to provide a holistic view of Forestry 4.0 from a forest supply chain perspective. The framework consists of four major components including the digital technologies pertinent to each of the supply chain business activities; the network infrastructure; the next generation system intelligence; and the collaborative forest supply chain digital ecosystem. These components are essential for the forest industry transformation to become truly interconnected among its supply chain actors. Some economic, environmental, and social expected benefits of Forestry 4.0 are discussed as well as potential impacts and challenges.


Author(s):  
Manman Wang ◽  
Feng Yang ◽  
Qiong Xia

D ifferent stakeholders pay more attention to consumer education for remanufacturing. They expect to promote the advancement of the remanufacturing industry by increasing the number of consumers willing to pay for remanufactured products. In the context of consumer education, this paper investigates the influence of different collection and remanufacturing capabilities on the reverse channel designs. The results show that increased consumer education makes the OEM partially forgo the remanufacturing right and more focus on the control of the collection process of reverse channels. We further explore the impact of consumer education on different stakeholders. We find that consumer education significantly improves individual profits and supply chain profit. However, for consumers, the temperate consumer education is all-around desirable, and excessive consumer education will reduce consumer surplus. For the environment, only when the environmental friendliness of RPs is relatively high, improving consumer education will reduce the environmental impact. Furthermore, we also examine the reverse channel designs from multiple criteria and discover that profitability, consumers, and environmental goals can be consistent under certain conditions. Our study provides new insights for the design of reverse channels in the context of consumer education.


2017 ◽  
Vol 117 (9) ◽  
pp. 1782-1799 ◽  
Author(s):  
Ahmed Mohammed ◽  
Qian Wang ◽  
Xiaodong Li

Purpose The purpose of this paper is to investigate the economic feasibility of a three-echelon Halal Meat Supply Chain (HMSC) network that is monitored by a proposed radio frequency identification (RFID)-based management system for enhancing the integrity traceability of Halal meat products and to maximize the average integrity number of Halal meat products, maximize the return of investment (ROI), maximize the capacity utilization of facilities and minimize the total investment cost of the proposed RFID-monitoring system. The location-allocation problem of facilities needs also to be resolved in conjunction with the quantity flow of Halal meat products from farms to abattoirs and from abattoirs to retailers. Design/methodology/approach First, a deterministic multi-objective mixed integer linear programming model was developed and used for optimizing the proposed RFID-based HMSC network toward a comprised solution based on four conflicting objectives as described above. Second, a stochastic programming model was developed and used for examining the impact on the number of Halal meat products by altering the value of integrity percentage. The ε-constraint approach and the modified weighted sum approach were proposed for acquisition of non-inferior solutions obtained from the developed models. Furthermore, the Max-Min approach was used for selecting the best solution among them. Findings The research outcome shows the applicability of the developed models using a real case study. Based on the computational results, a reasonable ROI can be achievable by implementing RFID into the HMSC network. Research limitations/implications This work addresses interesting avenues for further research on exploring the HMSC network design under different types of uncertainties and transportation means. Also, environmentalism has been becoming increasingly a significant global problem in the present century. Thus, the presented model could be extended to include the environmental aspects as an objective function. Practical implications The model can be utilized for food supply chain designers. Also, it could be applied to realistic problems in the field of supply chain management. Originality/value Although there were a few studies focusing on the configuration of a number of HMSC networks, this area is overlooked by researchers. The study shows the developed methodology can be a useful tool for designers to determine a cost-effective design of food supply chain networks.


2019 ◽  
Vol 2019 ◽  
pp. 1-19
Author(s):  
Yue Jiang ◽  
Yang Zhao ◽  
Mengyuan Dong ◽  
Shuihua Han

With the environment concern increasing, corporations are facing new challenges on carbon management in supply chain network. In this paper, environmental consideration is introduced to traditional supply chain management, and the sustainable supply chain (SSC) is designed considering carbon footprint. We develop a mixed integer linear programming (MILP) model to get the optimal decisions on partner selection, technology selection, and transportation mode selection, as well as material procurement, product supply, and recovery mode. For validating the model, a beverage company in China is used. We also analyze the impact of supply chain uncertainties such as carbon emission price and recovery rate of returned products on the decision of SSC design.


2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Yong Shin Park ◽  
Joseph Szmerekovsky ◽  
Alan Dybing

Faced with increasing concerns over the negative environmental impact due to human and industrial activities, biomass industry practitioners and policy makers have great interest in green supply chains to reduce carbon emissions from supply chain activities. There are many studies which model the biomass supply chain and its environmental impact. However, animal waste sourced biogas supply chain has not received much attention in the literature. Biogas from animal manure not only provides energy efficiency, but also minimizes carbon emissions compared to existing biomass products. Therefore, this study proposes a mixed integer linear program that minimizes total supply costs and carbon emissions from an animal waste sourced biogas supply chain while it also incorporates carbon price in the model to see the impact of a carbon policy on tactical and strategic supply chain decisions. To validate the model proposed, a case study of North Dakota is adopted where there is a high potential for a biogas plant to be developed. The results of our optimization experiment indicate that supply chain performance in terms of both costs and emissions is very sensitive to a carbon pricing mechanism.


2019 ◽  
Vol 14 (4) ◽  
pp. 841-871 ◽  
Author(s):  
Seyed Jafar Sadjadi ◽  
Zahra Ziaei ◽  
Mir Saman Pishvaee

Purpose This study aims to design a proper supply chain network for the vaccine industry in Iran, which considers several features such as uncertainties in demands and cost, perishability of vaccines, wastages in storage, limited capacity and different priorities for demands. Design/methodology/approach This study presents a mixed-integer linear programming (MILP) model and using a robust counterpart approach for coping with uncertainties of model. Findings The presented robust model in comparison with the deterministic model has a better performance and is more reliable for network design of vaccine supply chain. Originality/value This study considers uncertainty in the network design of vaccine supply chain for the first time in the vaccine context It presents an MILP model where strategic decisions for each echelon and tactical decisions among different echelons of supply chain are determined. Further, it models the difference between high- and low-priority demands for vaccine.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pravin Suryawanshi ◽  
Pankaj Dutta

PurposeThe emergence of risk in today's business environment is affecting every managerial decision, majorly due to globalization, disruptions, poor infrastructure, forecasting errors and different uncertainties. The impact of such disruptive events is significantly high for perishable items due to their susceptibility toward economic loss. This paper aims to design and address an operational planning problem of a perishable food supply chain (SC).Design/methodology/approachThe proposed model considers the simultaneous effect of disruption, random demand and deterioration of food items on business objectives under constrained conditions. The study describes this situation using a mixed-integer nonlinear program with a piecewise approximation algorithm. The proposed algorithm is easy to implement and competitive to handle stationary as well as nonstationary random variables in place of scenario techniques. The mathematical model includes a real-life case study from a kiwi fruit distribution industry.FindingsThe study quantifies the performance of SC in terms of SC cost and fill rate. Additionally, it investigates the effects of disruption due to suppliers, transport losses, product perishability and demand stochasticity. The model incorporates an incentive-based strategy to provide cost-cutting in the existing business plan considering the effect of deterioration. The study performs sensitivity analysis to show various “what-if” situations and derives implications for managerial insights.Originality/valueThe study contributes to the scant literature of quantitative modeling of food SC. The research work is original as it integrates a stochastic (uncertain) nature of SC simultaneously coupled with the effect of disruption, transport losses and product perishability. It incorporates proactive planning strategies to minimize the disruption impact and the concept of incremental quantity discounts on lot sizes at a destination node.


2018 ◽  
Vol 34 (1) ◽  
pp. 57-72 ◽  
Author(s):  
Michael David Berry ◽  
John Sessions

Abstract. This article presents an analysis of transportable biomass conversion facilities to evaluate the conceptual and economic viability of a highly mobile and modular biomass conversion supply chain in the Pacific Northwest of the United States. The goal of this work is to support a broader effort to more effectively and sustainably use residual biomass from commercial harvesting operations that are currently piled and burned as part of site preparation. A structural representation is first developed to include sources of biomass feedstock, distributed preprocessing hubs (centralized landings), and centralized processing facilities (biomass to product conversion sites) to produce desired products and byproducts. A facility costing model was developed to evaluate potential economics of scale, which then informed the optimization study. A mixed integer linear programming model was developed to characterize, evaluate, and optimize biomass collection, extraction, logistics, and facility placement over a regional landscape from a strategic level to evaluate the mobility concept. The objective was to minimize supply chain operational costs in order to quantify financial advantages and identify challenges of the proposed system modularity and mobility. A Lakeview, Oregon case study was evaluated with an assumed modular biochar facility servicing the region. In particular, we review economies of scale, mobility, energy costs, and biomass availability tradeoffs. This analysis points towards a modular system design of movement frequency between 1 to 2 years being most viable in the conditions evaluated. It was found that the impact of plant movement, scale, and biomass availability can increase supply chain costs by $11/BDMT ($10/BDT), $33/BDMT ($30/BDT), and $22/BDMT ($20/BDT) above the base case cost of $182/BDMT ($165/BDT) for a large-scale facility [45,000 BDMT yr-1(50,000 BDT yr-1)]in the conditions evaluated. Additionally, potential energy cost savings of a non-mobile modular stationary site as compared to one which utilizes off-grid electrical powers about $11/BDMT ($10/BDT) for a biochar facility. From the cases evaluated, a large-scale plant with limited mobility would be preferred under low availability of biomass conditions, whereas a stationary grid-connected plant would be more cost effective under higher availability conditions. Results depend greatly on the region, assumed harvest schedule, biomass composition, and governing biomass plant assumptions. Keywords: Biomass products, Biomass supply, Facility location, Mixed integer programming, Strategic planning, Transportable plants.


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