Shelf Life Considerations Research Articles

An Adaptive Sequential Decision-Making Approach for Perishable Food Procurement, Storage and Distribution Using Hyperconnected Logistics

The fast-food industry currently relies on frozen ingredients to reduce the cost of procurement of raw materials. In recent years, consumers have started to curb their habit of eating out from fast-food chain restaurants due to the growing concerns for unhealthy menu choices made primarily from highly processed and/or frozen food ingredients. To address these issues, some organizations in the fast-food industry have started to offer menus with fresh unfrozen ingredients sourced locally or regionally. This paper addresses the problem of integrating sourcing, storage, and distribution strategies for a fast-food restaurant chain at the regional level. We present an adaptive sequential optimization decision-making approach for procurement, storage, and distribution of perishable food products to multi-unit restaurants at the regional level. This solution approach uses shelf-life considerations in developing a procurement and distribution strategy for fresh produce in the era of hyperconnected logistics. Three models are developed using Mixed Integer Linear Programming (MILP). First, a procurement model is developed to find the cost-effective supplier for each produce category based on shelf life. Then, a distribution model is developed to find the cost-optimal solution for distributing produce to multiple restaurant locations considering weight, volume, and operation hours. Finally, an integrated model is developed to optimally combine procurement and distribution options generated by the first two models to minimize costs while respecting total shelf-life constraints. Numerical experiments based on realistic data are carried out to show that the proposed sequential approach yields valid decisions and presents the effects of price, shelf-life, and demand changes on the supply chain.

Coordinating visit interval and safety stock decisions in a two-level supply chain with shelf-life considerations

In many real-world situations, a distributor visits a downstream retailer to receive orders of products with fixed shelf-life and then delivers them after a lead-time. Under such circumstances, the retailer should determine its safety stock level by considering the demand uncertainty and the distributor's visit interval. In this paper, we coordinate the safety stock level of the retailer with the visit interval and the replenishment policy of the distributor, where the distributor is subject to two types of shelf-life constraints: (1) fixed shelf-life for the product, and (2) minimum remaining shelf life required by the retailer. A fair profit-sharing strategy is developed to coordinate the investigated SC and to encourage both members to participate in a joint decision-making scheme. The results reveal that the proposed coordination policy not only coordinates the SC of products with fixed shelf-life but also significantly improves the customer service level (CSL) and the profits of the entire SC and its agents. Further, sensitivity analyses have been carried out to analyze the performance of the proposed coordination model under different circumstances.

Washed red cells: theory and practice.

Washing of red cells is sometimes performed to reduce allergic reactions due to contaminating plasma proteins or to reduce the concentration of potassium accumulating in the supernatant of red cells during storage as an alternative to transfusion of fresher red cells in patients at risk of hyperkalaemia. There are a variety of methods for washing red cells, and the laboratory data suggest that variables such as age of red cell before washing, washing method and solution, storage medium and length of storage time after washing can all effect the final red cell quality. Studies suggest that washing removes 90-95% plasma, but the proportion of units below 0·05mg/dl IgA (equivalent to IgA deficient) is variable dependent upon methods used. Although potassium levels are reduced immediately following washing, the rate of leakage following subsequent storage is method-dependent, requiring careful consideration of shelf life if potassium reduction is the goal. Other markers of red cell quality such as haemolysis are negatively impacted by washing so a reduced shelf life compared to standard red cells is appropriate, especially following irradiation. Data from animal models and clinical studies on possible additional benefits of washing, such as reduced lung or kidney injury, are mixed, ranging from some benefit to some harm, and further studies are warranted.

Optimization of economic lot scheduling problem with backordering and shelf-life considerations using calibrated metaheuristic algorithms

This paper addresses the optimization of economic lot scheduling problem, where multiple items are produced on a single machine in a cyclical pattern. It is assumed that each item can be produced more than once in every cycle, each product has a shelf-life restriction, and backordering is permitted. The aim is to determine the optimal production rate, production frequency, cycle time, as well as a feasible manufacturing schedule for the family of items, and to minimize the long-run average costs. Efficient search procedures are presented to obtain the optimum solutions by employing four well-known metaheuristic algorithms, namely genetic algorithm (GA), particle swarm optimization (PSO), simulated annealing (SA), and artificial bee colony (ABC). Furthermore, to make the algorithms more effective, Taguchi method is employed to tune various parameters of the proposed algorithms. The computational performance and statistical optimization results show the effectiveness and superiority of the metaheuristic algorithms over other reported methods in the literature.

A time-varying lot size method for the economic lot scheduling problem with shelf life considerations

Most studies on the economic lot scheduling problem with shelf life considerations adopt the common cycle approach which usually gives a result with high cost. Basic period method has been applied to this problem recently resulting in a lower cost. This paper takes a time-varying lot size approach. Two models are formulated to optimise the production schedule for any given production sequence, one assuming that production of each product starts only when the inventory of this product becomes zero, and the other relaxing this restriction. To generate production sequences, we use an existing heuristic and also develop a new heuristic. Numerical experiments on a benchmark problem show that at all the utilisation levels tested the new method outperforms previous methods. Further experiments show that the production frequencies for the products, production sequence and a less restricted scheduling model all contribute to the low production cost. [Received: 22 August 2006; Revised: 28 October 2007; Accepted: 12 December 2007]

Mixed-Integer Linear Programming approaches to shelf-life-integrated planning and scheduling in yoghurt production

In the production of perishable products such as dairy, meat or bakery goods, the consideration of shelf life in production planning is of particular importance. Retail customers with relatively low inventory turns can benefit significantly from longer product shelf life as wastage and out-of-stock rates decrease. However, in today's production planning and control systems, shelf-life issues with regard to specific products or customers are only seldom accounted for. Therefore, the objective of this paper is to develop Mixed-Integer Linear Programming (MILP) models that integrate shelf-life issues into production planning and scheduling. The research is based on an industrial case study of yoghurt production. Relying on the principle of block planning, three different MILP models for weekly production planning are presented that apply a combination of a discrete and continuous representation of time. Overnight production and, hence, the necessity for identifying two different shelf-life values for the same production lot is included in the model formulation. Numerical experiments show that near-optimal solutions can be obtained within reasonable computational time.

A basic period approach to the economic lot scheduling problem with shelf life considerations

Almost all the research on the economic lot scheduling problem (ELSP) considering limited shelf life of products has assumed a common cycle approach and an unrealistic assumption of possibility of deliberately reducing the production rate. In many cases, like in food processing industry where limited shelf life for products is common, changing the production rates is not allowed at all because it may result in products with poor quality. In this paper, we allow products to be produced more than once in a cycle and do not allow reducing production rates. We present a modification to the Haessler's basic period procedure to account for the shelf life. Proposed ‘branch-and-bound like’ procedure exploits these extra constraints to efficiently achieve a feasible solution. Numerical examples are presented to show that our approach outperforms common cycle approach with shelf life considerations.

Incorporating planned backorders in a family production context with shelf-life considerations

This paper considers the problem of determining the optimal production rate for each item and the optimal cycle time for the family of items in a family production context with restrictions on the shelf-life of various items in the family. We investigate the impact of incorporating planned backorders into the system. We show that the model with planned backorders reduces to a model without backorders with modified holding costs and shelf-life. Therefore, the model with planned backorders can be analysed using the earlier model developed by Viswanathan and Goyal (1997). We also present several examples to demonstrate how incorporating planned backorders can reduce the total costs.

Optimal cycle time and production rate in a family production context with shelf life considerations

This paper considers the problem of determining the optimal production rate for each item and the optimalcycle time for the family of items in a family production context with restrictions on the shelf life of the various items in the family. An algorithm that determines the optimal production rate for all the items as well as the optimal cycle time is proposed. This is an improvement over the existing method by Silver (1995) that can determine the optimal production rate only for one item for which the shelf life constraint is binding. Examples are provided to illustrate the proposed method.

Shelf life considerations in a family production context

In this paper we consider a piece of manufacturing equipment dedicated to the production of a family of items. With known level demand rates for the individual items the policy used is to cycle through production of all of the items every T units of time. The paper addresses the choice among two adjustment options when the cost-minimizing T value leads to potential spoilage of an item because of shelf life considerations. The less obvious option of slowing the production rate of the concerned item is shown to be more cost effective than simply reducing the T value.