Planning of capacity, production and inventory decisions in a generic reverse supply chain under uncertain demand and returns (original) (raw)

Modular recycling supply chain under uncertainty: a robust optimisation approach

The International Journal of Advanced Manufacturing Technology, 2018

It is estimated that recycling can avert approximately 50% annual landfill cost, while simultaneously recovering lost materials valued at 4 to 9.5% of the total logistics network cost. This study proposes a robust integrated reverse logistics supply chain planning model with a modular product design at different quality levels. A mixed-integer programming (MIP) model is formulated to maximise the profit by considering the collection of returned products, the recovery of modules and the proportion of the product mix at different quality levels. This paper proposes the collection of returnable items (end-oflife, defective and under-warranty products) through retail outlets and the appropriate recovery of modules to manage these using a network of recovery service providers. The modular product design approach is adopted to create design criteria that provide an improved recovery process at a lower cost. This robust model seeks solutions close to the mathematically optimal solutions for a set of alternative scenarios identified by a decision-maker. The efficacy of the proposed model is evaluated by a given set of variously sized numerical expressions and sensitivity analyses. A robust solution is found that appraises the impact of two major sources of uncertainty, demand rate and the volume of returned products of a key recycled material.

Production planning of a hybrid manufacturing–remanufacturing system under uncertainty within a closed-loop supply chain

This paper deals with the production planning and control of a single product involving combined manufacturing and remanufacturing operations within a closed-loop reverse logistics network with machines subject to random failures and repairs. While consumers traditionally dispose of products at the end of their life cycle, recovery of the used products may be economically more attractive than disposal, while remanufacturing of the products also pursues sustainable development goals. Three types of inventories are involved in this network. The manufactured and remanufactured items are stored in the first and second inventories. The returned products are collected in the third inventory and then remanufactured or disposed of. The objective of this research is to propose a manufacturing/remanufacturing policy that would minimize the sum of the holding and backlog costs for manufacturing and remanufacturing products. The decision variables are the production rates of the manufacturing and the remanufacturing machines. The optimality conditions are developed using the optimal control theory based on stochastic dynamic programming. A computational algorithm, based on numerical methods, is used for solving the optimal control problem. Finally, a numerical example and a sensitivity analysis are presented to illustrate the usefulness of the proposed approach. The structure of the optimal control policy is discussed depending on the value of costs and parameters and extensions to more complex reverse logistics networks are discussed.

Optimum Scenarios Evaluation of Reverse Logistics Systems under Influence of Uncertainties : Decisions made on Operating Costs

2017

A time-discrete, constrained, Linear Quadratic Gaussian (LQG) production planning problem is formulated to develop a production plan with sub-optimal levels of production and remanufacturing for a single product. With the objective to define a strategy of remanufacturing used product, estimated return rates are used to provide production scenarios based on this plan. Nowadays, specific legislation is applied to many industrial sectors regard to the return of used products. Thus, motivated by environmental factors and a shortage of raw materials, partial or total reuse of return products are a high priority on business's agenda of many companies. This paper uses an approach of literature to solve a production-planning problem of a dynamic system that includes a reverse channel, with a remanufacturing facility. It is assumed that fluctuations of demand for serviceable products are approximated by stationary normal random variables. Thus, the constrained LQG problem here considered...

Mathematical Decision Model for Reverse Supply Chains Inventory

International Journal of Computers Communications & Control, 2014

In the reverse supply chain inventory theory, inventory models are concerned with the demand of reusable parts, stock replenishment, ordering cycle, delivery lead time, number of disassembled products, ordering costs. The particularity of these models consists in the occurrence of high uncertainties of the quantity and quality of the returned products and resulting parts. To overcome the problem, an inventory model that incorporates decision variables at proactive and reactive levels is derived and discussed in this paper.

A Two-Stage Stochastic Model for the Design and Planning of a Multi-Product Closed Loop Supply Chains

2012

In this paper we address the problem of uncertainty in the design and planning of a multi-period, multi-product closed loop supply chain, where the recovered products are end-of-life products that are disassembled and recycled. Uncertainty is explicitly modelled by considering customers' demands and returns to be stochastic. A two-stage model is developed where first stage decisions concern the facility location while second stage decisions are the production planning of the supply chain. The integer Lshaped method was adopted as the solution tool and computational tests were performed on multi-period and multi-commodity networks randomly generated based on a reference case. A comparison between the proposed solution method and the straight use of the CPLEX is performed.

Optimization of a Stochastic Reverse Logistics Network with Refurbishment and Exchange Options

SSRN Electronic Journal, 2000

Remanufacturing activities are gaining momentum in the manufacturing industry. Therefore, the need for optimized networks becomes more pressing. In this paper we take a profit maximization approach to simultaneously determine the optimal network and the delivery strategy to support remanufacturing services offered to customers. In order to set up a network, investment decisions have to be made concerning the number, locations and types of remanufacturing facilities. Additionally, appropriate capacity and inventory levels have to be set in order to guarantee a given service level. These network decisions are influenced by the way the remanufacturing services are offered by the manufacturing firm. We consider two possible service delivery strategies: the service provider can either make a quick exchange of the used part by a refurbished one or re-install the original part after remanufacturing it. The model described in this paper is applied to optimize the network and service delivery strategy at a worldwide manufacturer of construction, mining and industrial equipment.

Redesign of a sustainable reverse supply chain under uncertainty: A case study

Journal of Cleaner Production, 2017

This paper presents a Stochastic Multi-Objective Mixed Integer Non-Linear Problem (SMOMINLP) to redesign the sustainable supply chain to recycle certain products. The model integrates economic, environmental and social objectives to support strategic decisions such as facility location, material flow design and transport selection. The environmental impact objective is calculated through the Life Cycle Assessment (LCA) methodology using the Eco-indicator 99 method. A multi-criteria programming approach algorithm to manage several objectives linked with stochastic programming to address uncertainty is developed in this investigation. In addition, to assess the solutions obtained and to reduce the uncertainty effect on decision-making, a performance indicator is proposed. Model feasibility has been tested in Cuba. In this case study, the redesign of a supply chain for plastic recycling is examined. The experimental results show supply chain configurations that improve sustainability performance.

Dynamic reverse supply chain network design under uncertainty: mathematical modeling and solution algorithm

International Transactions in Operational Research, 2020

Motivated by the recovery of modular-structured products, this study addresses the flexible design of a reverse supply chain (RSC) over a planning horizon while incorporating the dynamic uncertain behavior of product returns. The stochastic parameter is modeled as a scenario tree and therefore the concerned problem is formulated as a multistage mixed-integer stochastic program. To alleviate the computational complexity of the proposed model, it is decomposed into smaller scenario cluster submodels associated with a number of subtrees that share a certain number of predecessor nodes in the original scenario tree. The submodels are coordinated into an implementable solution via a Lagrangian-progressive hedging-based method that employs a viable Benders decomposition based algorithm for solving each scenario cluster submodel. Based on a realistic scale case, computational results indicate the superiority of the proposed flexible dynamic RSC design model compared to the existing models. Results also demonstrate the efficiency of the proposed solution approach.

A mixed integer programming model for remanufacturing in reverse logistics environment

International Journal of Advanced Manufacturing Technology, 2008

Recently, there has been a growing interest in reverse logistics due to environmental deterioration. Firms incorporate reverse flow to their systems for such reasons as ecological and economic factors, government regulations and social responsibilities. In this paper a new mixed integer mathematical model for a remanufacturing system, which includes both forward and reverse flows, is proposed and illustrated on a numerical example. The proposed model provides the optimal values of production and transportation quantities of manufactured and remanufactured products while solving the location problem of dissassembly, collection and distribution facilities. The model is validated by using a set of experimental data reflecting practical business situation. Sensitivity analysis of the model is also presented.

A system dynamics model for dynamic capacity planning of remanufacturing in closed-loop supply chains

Computers & Operations Research, 2007

Product recovery operations in reverse supply chains face continually and rapidly changing product demand characterized by an ever increasing number of product offerings with reduced lifecycles due to both technological advancements and environmental concerns. Capacity planning is a strategic issue of increased complexity importance for the profitability of reverse supply chains due to their highly variable return flows. In this work we tackle the development of efficient capacity planning policies for remanufacturing facilities in reverse supply chains, taking into account not only economic but also environmental issues, such as the take-back obligation imposed by legislation and the "green image" effect on customer demand. The behavior of the generic system under study is analyzed through a simulation model based on the principles of the system dynamics methodology. The simulation model provides an experimental tool, which can be used to evaluate alternative long-term capacity planning policies ("what-if" analysis) using total supply chain profit as measure of policy effectiveness. Validation and numerical experimentation further illustrate the applicability of the developed methodology, while providing additional intuitively sound insights.