In this paper, we present a new multi-commodity network flow-based formulation for the multi-period cell formation problem. The objective of the model is to minimize the total costs of acquisition, ...disposal, and relocation of machines, manufacturing, and inter-cell/intra-cell material handling. The main contribution of this paper comes from the fact that we structure the underlying problem as a multi-period multi-commodity network flow problem with general integer variables for machine acquisition, disposal, and relocation connecting one period to the next. This formulation is more efficient than the formulations we have encountered in the literature. Another contribution of this paper is that the flow variables representing the flow of parts through the system is path based; as a result, this approach makes it very easy to model alternate process routings. This paper illustrates the formulation by the use of two examples taken from the literature and presents computational results for other representative problems.
The fresh fruit agricultural and distribution sector is faced with risks and uncertainties from climate change, water scarcity, land-use increase for industrial and urban development, consumer ...behavior, and price volatility. The planning framework for production and distribution is highly complex as a result. Mathematical models have been developed over the decades to deal with this complexity. With improvements in both processor speed and memory, these models are becoming increasingly sophisticated. This review focuses on the recent progress in mathematically based decision making to account for uncertainties in the fresh fruit supply chain. The models in the literature are mostly based on linear and mixed integer programming and involve variants such as stochastic programming and robust optimization. The functional areas of application include planting, harvest optimization, logistics and distribution. The perishability of the fresh fruit supply chain is an important issue as is the cycle time of cultivation and harvest.
The process of remanufacturing is attractive economically and environmentally for both manufacturers and customers. This paper addresses a problem in the repairable spare parts remanufacturing ...industry to find the cost-optimal production strategy incorporating reconditioned components. New and reconditioned components are used to carry out replacements in order to honor warranty commitments. Key production decisions, such as when remanufacturing should commence, how long the warranty period should be, and how many returned components should be reconditioned are considered. The availability of reconditioned components and their discounted costs are also incorporated in the mathematical model. The goal is to investigate the interaction between these decisions and their impacts on the manufacturing system and the customer. An application to the remanufacturing of rotable spare parts in the airline industry is presented.
The design of reverse logistics and remanufacturing processes and the recovery of end-of-life products have been well-studied in the literature. Quality, reliability, maintenance and warranty for ...recovered products and the remanufacturing activities that extend their life are integral issues in reverse logistics. This paper reviews recent and relevant literature on these issues in closed-loop supply chains, with a focus on remanufactured or second-hand products. The published literature is first classified into domain areas of research and practice. The wide array of mathematical tools and techniques used in the literature are then identified and mapped. Finally, the findings are summarised and the main research gaps are highlighted.
•A multiperiod multiobjective distributionally robust optimization model is proposed.•Goal is to enhance healthcare supply chain resilience during the COVID-19 pandemic.•Study is inspired by a ...Canadian healthcare provider facing PPE supply uncertainty.•Assesses trade-off between cost and service level using multiobjective optimization.•Reduces relative cost variance using distributionally robust optimization.
This paper presents a multi-period multi-objective distributionally robust optimization framework for enhancing the resilience of personal protective equipment (PPE) supply chains against disruptions caused by pandemics. The research is motivated by and addresses the supply chain challenges encountered by a Canadian provincial healthcare provider during the COVID-19 pandemic. Supply, price, and demand of PPE are the uncertain parameters. The ∊-constraint method is implemented to generate efficient solutions along the trade-off between cost minimization and service level maximization. Decision makers can easily adjust model conservatism through the ambiguity set size parameter. Experiments investigate the effects of model conservatism on optimal procurement decisions such as the portion of the supply base dedicated to long-term fixed contracts. Other types of PPE sources considered by the model are one-time open-market purchases and federal emergency PPE stockpiles. The study recommends that during pandemics health care providers use distributionally robust optimization with the ambiguity set size falling in one of three intervals based on decision makers’ relative preferences for average cost performance, worst-case cost performance, or cost variance. The study also highlights the importance of surveillance and early warning systems to allow supply chain decision makers to trigger contingency plans such as locking contracts, reinforcing logistical capacities and drawing from emergency stockpiles. These emergency stockpiles are shown to play efficient hedging functions in allowing healthcare supply chain decision makers to compensate variations in deliveries from contract and open-market suppliers.
•The selective maintenance problem for large serial k-out-of-n:G systems is studied.•Imperfect maintenance levels are considered for both PM and CM actions.•Two nonlinear and two BIP formulations are ...proposed.•Experiments show the efficiency of the new 2-phase approach for complex structures.
The selective maintenance problem (SMP) arises in many large multicomponent systems which are operated for consecutive missions interspersed with finite breaks during which only a selected set of component repairs or replacements can be carried out due to limited time, budget, or resources. The problem is to decide which components and degree of repairs should be performed in order to guarantee a pre-specified performance level during the subsequent mission. Current SMP formulations in the literature are nonlinear, deal mainly with basic or series-parallel systems and mostly use heuristic methods to obtain solutions.
This paper introduces the first SMP model for serial k-out-of-n systems. Two nonlinear formulations are developed, which can be used to solve the problem for small to moderate size k-out-of-n systems. For large k-out-of-n systems or complex reliability structures, we develop a new two-phase approach which transforms the problem into a multidimensional multiple-choice knapsack problem (MMKP). The new approach is shown to be efficient through multiple sets of numerical experiments.
Extended warranties are widely adopted and accepted in the marketplace by manufacturers and retailers as it helps to enhance the customers' post-sale satisfaction. In closed-loop supply chains, the ...extended warranty not only generates profit for the manufacturer, but also provides warranty returns of the new products for remanufacturing. In this paper, a two-period model is developed and optimal pricing strategies for the extended warranties are derived. We compare the optimal pricing and retailing strategies of the extended warranties for remanufactured and new products offered by the manufacturer with and without the retailer's own extended warranty while considering the competition between the manufacturer and the retailer for the extended warranty of new products. We find that the introduction of the retailer's extended warranty does not always hurt the manufacturer's profit. Numerical analyses also show that there exists an optimal extended warranty length for the manufacturer that maximises its profit. Moreover, we show that the retailer cannot extract more profit by increasing the length of its own extended warranty.
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