Analysis of postponement strategy for perishable items by EOQ-based models

2006-2007 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Energy and Carbon Dioxide Impacts from Lean Logistics and Retailing Systems: A Discrete-event Simulation Approach for the Consumer Goods Industry

abstract: Consumer goods supply chains have gradually incorporated lean manufacturing principles to identify and reduce non-value-added activities. Companies implementing lean practices have experienced improvements in cost, quality, and demand responsiveness. However certain elements of these practices, especially those related to transportation and distribution may have detrimental impact on the environment. This study asks: What impact do current best practices in lean logistics and retailing have on environmental performance? The research hypothesis of this dissertation establishes that lean distribution of durable and consumable goods can result in an increased amount of carbon dioxide emissions, leading to climate change and natural resource depletion impacts, while lean retailing operations can reduce carbon emissions. Distribution and retailing phases of the life cycle are characterized in a two-echelon supply chain discrete-event simulation modeled after current operations from leading organizations based in the U.S. Southwest. By conducting an overview of critical sustainability issues and their relationship with consumer products, it is possible to address the environmental implications of lean logistics and retailing operations. Provided the waste reduction nature from lean manufacturing, four lean best practices are examined in detail in order to formulate specific research propositions. These propositions are integrated into an experimental design linking annual carbon dioxide equivalent emissions to: (1) shipment frequency between supply chain partners, (2) proximity between decoupling point of products and final customers, (3) inventory turns at the warehousing level, and (4) degree of supplier integration. All propositions are tested through the use of the simulation model. Results confirmed the four research propositions. Furthermore, they suggest synergy between product shipment frequency among supply chain partners and product management due to lean retailing practices. In addition, the study confirms prior research speculations about the potential carbon intensity from transportation operations subject to lean principles.Dissertation/ThesisPh.D. Sustainability 201

Stochastic make-to-stock inventory deployment problem: an endosymbiotic psychoclonal algorithm based approach

Integrated steel manufacturers (ISMs) have no specific product, they just produce finished product from the ore. This enhances the uncertainty prevailing in the ISM regarding the nature of the finished product and significant demand by customers. At present low cost mini-mills are giving firm competition to ISMs in terms of cost, and this has compelled the ISM industry to target customers who want exotic products and faster reliable deliveries. To meet this objective, ISMs are exploring the option of satisfying part of their demand by converting strategically placed products, this helps in increasing the variability of product produced by the ISM in a short lead time. In this paper the authors have proposed a new hybrid evolutionary algorithm named endosymbiotic-psychoclonal (ESPC) to decide what and how much to stock as a semi-product in inventory. In the proposed theory, the ability of previously proposed psychoclonal algorithms to exploit the search space has been increased by making antibodies and antigen more co-operative interacting species. The efficacy of the proposed algorithm has been tested on randomly generated datasets and the results compared with other evolutionary algorithms such as genetic algorithms (GA) and simulated annealing (SA). The comparison of ESPC with GA and SA proves the superiority of the proposed algorithm both in terms of quality of the solution obtained and convergence time required to reach the optimal/near optimal value of the solution

The responsive reply chain: the influence of the positioning of decoupling points

Manufacturing supply chains have been challenged by high competition, dynamic, and stochastic conditions. They have to be constantly responsive in today’s ever-changing manufacturing environment. The proper positioning of decoupling points for material flow and information flow has a significant potential for increasing responsiveness in a supply chain. Positioning the material decoupling point as close to the end consumer as possible whilst the information decoupling point is positioned upstream is the key to the industries’ ability to reduce lead time and enhance performance in the dynamic behaviour of the supply chain. [Continues.

Water Management and the Valuation of Indirect Environmental Services

Comprehensive water basin and watershed planning and management require valuation of the intermediate ecological services provided to the water resources themselves. Valuation of forest cover in the augmentation of water resources is discussed in the context of aggregate economic planning, water-basin or sectoral planning, and conservation project evaluation. The importance of valuing intermediate non-market goods is illustrated for each planning tool in the context of an illustrative example of the Pearl Harbor/Ko'olau watershed in Hawaii. In the context of water allocation and investment in waterworks, considerations of full income valuation imply that the value of water should incorporate the risk of watershed degradation contingent on the expected conservation effort. What appear to be new objectives of economic planning, such as sustainable development, do not require new criteria but rather the augmentation of existing methods of income accounting and project valuation to include the values on non-market goods. We also show that measurement of non-market valuation does not necessarily require the use of contingent-valuation methods, even when the usual alternatives (hedonics, household production, etc.) are not directly applicable.

An ESPC algorithm based approach to solve inventory deployment problem

Global competitiveness has enforced the hefty industries to become more customized. To compete in the market they are targeting the customers who want exotic products, and faster and reliable deliveries. Industries are exploring the option of satisfying a portion of their demand by converting strategically placed products, this helps in increasing the variability of product produced by them in short lead time. In this paper, authors have proposed a new hybrid evolutionary algorithm named Endosymbiotic-Psychoclonal (ESPC) algorithm to determine the amount and type of product to stock as a semi product in inventory. In the proposed work the ability of previously proposed Psychoclonal algorithm to exploit the search space has been increased by making antibodies and antigen more cooperative interacting species. The efficacy of the proposed algorithm has been tested on randomly generated datasets and the results obtained, are compared with other evolutionary algorithms such as Genetic Algorithm (GA) and Simulated Annealing (SA). The comparison of ESPC with GA and SA proves the superiority of the proposed algorithm both in terms of quality of the solution obtained, and convergence time required to reach the optimal /near optimal value of the solution

Supply Chain Management Under The Threat Of International Terrorism

On the morning of September 11th, 2001, the United States and the Western world entered into a new era – one in which large scale terrorist acts are to be expected. The impacts of the new era will challenge supply chain managers to adjust relations with suppliers and customers, contend with transportation difficulties and amend inventory management strategies. This paper looks at the twin corporate challenges of (i) preparing to deal with the aftermath of terrorist attacks and (ii) operating under heightened security. The first challenge involves setting certain operational redundancies. The second means less reliable lead times and less certain demand scenarios. In addition, the paper looks at how companies should organize to meet those challenges efficiently and suggests a new public-private partnership. While the paper is focused on the US, it has worldwide implications

A Computer-Based Simulation Investigation of Environment-Strategy Fit for Risk Management in Global Supply Chains

The purpose of this dissertation is to examine the phenomenon of risk management in global supply chains. Drawing from logistics, supply chain management, operations management, economics, international business, and strategy literatures and a qualitative study, a comprehensive conceptual model of environment-strategy fit for risk management in global supply chains was developed. External environmental conditions comprising of supply and demand risks, four risk management strategies, namely hedging, assuming, postponement, and speculation, and a moderator in the form of a port disruption were chosen for further investigation. The model was quantitatively tested using a simulation. The findings from this dissertation study reflect mixed results. Findings that conform to existing research, primarily related to hedging and speculation strategies, provide empirical support for extant knowledge that is primarily conceptual or experience-based. On the other hand, findings that are contrary to existing knowledge or are supported under very select conditions, primarily related to assuming and postponement strategies, provide interesting new insights into the phenomenon. The findings add to both theoretical and practical understanding of the phenomenon. This research opens up several new research directions that indicate that continued research is needed to facilitate both theoretical and empirical progress in better understanding of risk management in global supply chains

A delayed differentiation multi-product FPR model with scrap and a multi-delivery policy – II: Using two-machine production scheme

This paper concerns a delayed differentiation multi-product finite production rate (FPR) model with scrap and multi-delivery policy using a two-machine production scheme. Conventional FPR model considers a single product, single-stage production with all products fabricated being of perfect quality, and product demand satisfied by a continuous inventory issuing policy. However, in real vendor-buyer integrated systems, most vendors would adopt a multi-product production plan to maximize machine utilization. They often use a periodic or multi-shipment policy to distribute their finished products. When planning to produce a cluster of multiple products that share a common intermediate part, the vendor would often evaluate a two-stage production scheme. The first stage manufactures only the common parts for all products and the second stage separately manufactures the end products. The aim is to shorten the replenishment cycle time and reduce overall production-inventory related costs. This study considers a two-machine production scheme and the two-stage production process with the objective of determining the optimal production cycle time and number of deliveries. A numerical example with sensitivity analysis is provided to demonstrate practical use of the obtained results as well as to compare the proposed production scheme to that of using a single machine in the multi-product two-stage FPR model