Production distribution planning in a multiechelon supply chain using carbon policies: A review and reflections

Sustainability of a supply chain has gained more attention from economists, environmentalists, consumers, manufacturers, government and the academia. In this paper, the literature survey has been performed on production allocation problem in a multi-echelon supply chain with carbon policies. With web-based search engines such as Scopus and Web of Science several resources such as journals, conference proceedings and books are selected and reviewed. It is observed from the literature that the mentioned problem traces the progression of carbon policies in a supply chain over the past 22 years to provide substantiation for Green Supply Chain. The research papers are then analyzed and categorized to construct the useful foundation of previous studies. Moreover, the importance of this problem in recent years needs has been highlighted by mentioning the gaps in the literature. Further, at the end of the paper, several future work directions in this area also suggested.(undefined)info:eu-repo/semantics/publishedVersio

Non-stationary stochastic inventory lot-sizing with emission and service level constraints in a carbon cap-and-trade system

Firms worldwide are taking major initiatives to reduce the carbon footprint of their supply chains in response to the growing governmental and consumer pressures. In real life, these supply chains face stochastic and non-stationary demand but most of the studies on inventory lot-sizing problem with emission concerns consider deterministic demand. In this paper, we study the inventory lot-sizing problem under non-stationary stochastic demand condition with emission and cycle service level constraints considering carbon cap-and-trade regulatory mechanism. Using a mixed integer linear programming model, this paper aims to investigate the effects of emission parameters, product- and system-related features on the supply chain performance through extensive computational experiments to cover general type business settings and not a specific scenario. Results show that cycle service level and demand coefficient of variation have significant impacts on total cost and emission irrespective of level of demand variability while the impact of product’s demand pattern is significant only at lower level of demand variability. Finally, results also show that increasing value of carbon price reduces total cost, total emission and total inventory and the scope of emission reduction by increasing carbon price is greater at higher levels of cycle service level and demand coefficient of variation.The analysis of results helps supply chain managers to take right decision in different demand and service level situations

Green supply chain quantitative models for sustainable inventory management: A review

[EN] This paper provides a systematic and up-to-date review and classification of 91 studies on quantitative methods of green supply chains for sustainable inventory management. It particularly identifies the main study areas, findings and quantitative models by setting a point for future research opportunities in sustainable inventory management. It seeks to review the quantitative methods that can better contribute to deal with the environmental impact challenge. More specifically, it focuses on different supply chain designs (green supply chain, sustainable supply chain, reverse logistics, closed-loop supply chain) in a broader application context. It also identifies the most important variables and parameters in inventory modelling from a sustainable perspective. The paper also includes a comparative analysis of the different mathematical programming, simulation and statistical models, and their solution approach, with exact methods, simulation, heuristic or meta-heuristic solution algorithms, the last of which indicate the increasing attention paid by researchers in recent years. The main findings recognise mixed integer linear programming models supported by heuristic and metaheuristic algorithms as the most widely used modelling approach. Minimisation of costs and greenhouse gas emissions are the main objectives of the reviewed approaches, while social aspects are hardly addressed. The main contemplated inventory management parameters are holding costs, quantity to order, safety stock and backorders. Demand is the most frequently shared information. Finally, tactical decisions, as opposed to strategical and operational decisions, are the main ones.The research leading to these results received funding from the Grant RTI2018-101344-B-I00 funded by MCIN/AEI/10.13039/501100011033 and by "ERDF A way of making Europe". It was also funded by the National Agency for Research and Development (ANID) / Scholarship Program/Doctorado Becas en el Extranjero/2020 72210174.Becerra, P.; Mula, J.; Sanchis, R. (2021). Green supply chain quantitative models for sustainable inventory management: A review. Journal of Cleaner Production. 328:1-16. https://doi.org/10.1016/j.jclepro.2021.129544S11632

Programming problems on time scales: Theory and computation

In this dissertation, novel formulations for several classes of programming problems are derived and proved using the time scales technique. The new formulations unify the discrete and continuous programming models and extend them to other cases in between. Moreover, the new formulations yield the exact optimal solution for the programming problems on arbitrary isolated time scales, which solve an important open problem. Throughout this dissertation, six distinct classes of programming problems are presented as follows. First, the primal as well as the dual time scales linear programming models on arbitrary time scales are formulated. Second, separated linear programming primal and dual models have been established using the time scales approach. Third, state-constraints separated linear programming primal and dual models on time scales are considered. Fourth, linear fractional primal and dual models have been constructed on time scales. Fifth, quadratic programming problems are formulated using the time scales technique. Sixth, quadratic fractional programming problems have been constructed using a hybrid of the parametric approach and the time scales technique. In addition, for each class of these programming problems the weak duality theorem and the optimality conditions theorem are established for arbitrary time scales, while the strong duality theorem is given for isolated time scales to ensure that our formulation is indeed a perfect formulation. Furthermore, examples for the most well-known isolated time scales are given to illustrate the main results --Abstract, page iv

Non-stationary stochastic inventory lot-sizing with emission and service level constraints in a carbon cap-and-trade system

Firms worldwide are taking major initiatives to reduce the carbon footprint of their supply chains in response to the growing governmental and consumer pressures. In real life, these supply chains face stochastic and non-stationary demand but most of the studies on inventory lot-sizing problem with emission concerns consider deterministic demand. In this paper, we study the inventory lot-sizing problem under non-stationary stochastic demand condition with emission and cycle service level constraints considering carbon cap-and-trade regulatory mechanism. Using a mixed integer linear programming model, this paper aims to investigate the effects of emission parameters, product- and system-related features on the supply chain performance through extensive computational experiments to cover general type business settings and not a specific scenario. Results show that cycle service level and demand coefficient of variation have significant impacts on total cost and emission irrespective of level of demand variability while the impact of product's demand pattern is significant only at lower level of demand variability. Finally, results also show that increasing value of carbon price reduces total cost, total emission and total inventory and the scope of emission reduction by increasing carbon price is greater at higher levels of cycle service level and demand coefficient of variation. The analysis of results helps supply chain managers to take right decision in different demand and service level situations

Application of Optimization in Production, Logistics, Inventory, Supply Chain Management and Block Chain

The evolution of industrial development since the 18th century is now experiencing the fourth industrial revolution. The effect of the development has propagated into almost every sector of the industry. From inventory to the circular economy, the effectiveness of technology has been fruitful for industry. The recent trends in research, with new ideas and methodologies, are included in this book. Several new ideas and business strategies are developed in the area of the supply chain management, logistics, optimization, and forecasting for the improvement of the economy of the society and the environment. The proposed technologies and ideas are either novel or help modify several other new ideas. Different real life problems with different dimensions are discussed in the book so that readers may connect with the recent issues in society and industry. The collection of the articles provides a glimpse into the new research trends in technology, business, and the environment

Responsible Inventory Models for Operation and Logistics Management

The industrialization and the subsequent economic development occurred in the last century have led industrialized societies to pursue increasingly higher economic and financial goals, laying temporarily aside the safeguard of the environment and the defense of human health. However, over the last decade, modern societies have begun to reconsider the importance of social and environmental issues nearby the economic and financial goals. In the real industrial environment as well as in today research activities, new concepts have been introduced, such as sustainable development (SD), green supply chain and ergonomics of the workplace. The notion of “triple bottom line” (3BL) accounting has become increasingly important in industrial management over the last few years (Norman and MacDonald, 2004). The main idea behind the 3BL paradigm is that companies’ ultimate success should not be measured only by the traditional financial results, but also by their ethical and environmental performances. Social and environmental responsibility is essential because a healthy society cannot be achieved and maintained if the population is in poor health. The increasing interest in sustainable development spurs companies and researchers to treat operations management and logistics decisions as a whole by integrating economic, environmental, and social goals (Bouchery et al., 2012). Because of the wideness of the field under consideration, this Ph.D. thesis focuses on a restricted selection of topics, that is Inventory Management and in particular the Lot Sizing problem. The lot sizing problem is undoubtedly one of the most traditional operations management interests, so much so that the first research about lot sizing has been faced more than one century ago (Harris, 1913). The main objectives of this thesis are listed below: 1) The study and the detailed analysis of the existing literature concerning Inventory Management and Lot Sizing, supporting the management of production and logistics activities. In particular, this thesis aims to highlight the different factors and decision-making approaches behind the existing models in the literature. Moreover, it develops a conceptual framework identifying the associated sub-problems, the decision variables and the sources of sustainable achievement in the logistics decisions. The last part of the literature analysis outlines the requirements for future researches. 2) The development of new computational models supporting the Inventory Management and Sustainable Lot Sizing. As a result, an integrated methodological procedure has been developed by making a complete mathematical modeling of the Sustainable Lot Sizing problem. Such a method has been properly validated with data derived from real cases. 3) Understanding and applying the multi-objective optimization techniques, in order to analyze the economic, environmental and social impacts derived from choices concerning the supply, transport and management of incoming materials to a production system. 4) The analysis of the feasibility and convenience of governmental systems of incentives to promote the reduction of emissions owing to the procurement and storage of purchasing materials. A new method based on the multi-objective theory is presented by applying the models developed and by conducting a sensitivity analysis. This method is able to quantify the effectiveness of carbon reduction incentives on varying the input parameters of the problem. 5) Extending the method developed in the first part of the research for the “Single-buyer” case in a "multi-buyer" optics, by introducing the possibility of Horizontal Cooperation. A kind of cooperation among companies in different stages of the purchasing and transportation of raw materials and components on a global scale is the Haulage Sharing approach which is here taken into consideration in depth. This research was supported by a fruitful collaboration with Prof. Robert W. Grubbström (University of Linkoping, Sweden) and its aim has been from the beginning to make a breakthrough both in the theoretical basis concerning sustainable Lot Sizing, and in the subsequent practical application in today industrial contexts

Partner selection in sustainable supply chains: a fuzzy ensemble learning model

With the increasing demands on businesses to operate more sustainably, firms must ensure that the performance of their whole supply chain in sustainability is optimized. As partner selection is critical to supply chain management, focal firms now need to select supply chain partners that can offer a high level of competence in sustainability. This paper proposes a novel multi-partner classification model for the partner qualification and classification process, combining ensemble learning technology and fuzzy set theory. The proposed model enables potential partners to be classified into one of four categories (strategic partner, preference partner, leverage partner and routine partner), thereby allowing distinctive partner management strategies to be applied for each category. The model provides for the simultaneous optimization of both efficiency in its use of multi-partner and multi-dimension evaluation data, and effectiveness in dealing with the vagueness and uncertainty of linguistic commentary data. Compared to more conventional methods, the proposed model has the advantage of offering a simple classification and a stable prediction performance. The practical efficacy of the model is illustrated by an application in a listed electronic equipment and instrument manufacturing company based in southeastern China

Modelling and Determining Inventory Decisions for Improved Sustainability in Perishable Food Supply Chains

Since the introduction of sustainable development, industries have witnessed significant sustainability challenges. Literature shows that the food industry is concerned about its need for efficient and effective management practices in dealing with perishability and the requirements for conditioned storage and transport of food products that effect the environment. Hence, the environmental part of sustainability demonstrates its significance in this industrial sector. Despite this, there has been little research into environmentally sustainable inventory management of deteriorating items. This thesis presents mathematical modelling based research for production inventory systems in perishable food supply chains. In this study, multi-objective mixed-integer linear programming models are developed to determine economically and environmentally optimal production and inventory decisions for a two-echelon supply chain. The supply chain consists of single sourcing suppliers for raw materials and a producer who operates under a make-to-stock or make-to-order strategy. The demand facing the producer is non-stationary stochastic in nature and has requirements in terms of service level and the remaining shelf life of the marketed products. Using data from the literature, numerical examples are given in order to test and analyse these models. The computational experiments show that operational adjustments in cases where emission and cost parameters were not strongly correlated with supply chain collaboration (where suppliers and a producer operate under centralised control), emissions are effectively reduced without a significant increase in cost. The findings show that assigning a high disposal cost, limit or high weight of importance to perished goods leads to appropriate reduction of expected waste in the supply chain with no major cost increase. The research has made contributions to the literature on sustainable production and inventory management; providing formal models that can be used as an aid to understanding and as a tool for planning and improving sustainable production and inventory control in supply chains involving deteriorating items, in particular with perishable food supply chains.the Ministry of Science and Technology, the Royal Thai Government