Perishable Goods Supply Chain Research Articles

An integrated planning approach for perishable goods with stochastic lifespan: Production, inventory, and routing

This paper focuses on addressing the crucial challenges posed by the uncertainty surrounding perishable goods within the supply chain. With staggering socioeconomic costs and significant environmental implications, effective management of perishable goods emerges as a critical imperative. Globally, the annual loss of approximately 14% of food, amounting to a staggering USD 1 trillion, highlights the urgency of the issue. However, Prevailing classification methods for perishable products oversimplify their complexity by dividing them into fixed or variable lifespans, neglecting the random lifespans endured due to fluctuating storage conditions, blurring traditional boundaries between fixed and variable classifications. In response to these pressing challenges, the research proposes a novel approach: the development of a nonlinear mixed-integer programming model for a green closed-loop supply chain. This innovative model seamlessly integrates production, inventory, and routing decisions for both main and secondary products of a manufacturer. Moreover, it optimizes order splitting and transportation modes to efficiently convert perished items into raw materials under conditions of uncertainty. Central to the approach is the adoption of a scenario-based methodology to model uncertainties, particularly focusing on the variability in the lifespan of perishable products. This approach allows for a more nuanced understanding of the complex dynamics inherent in managing perishable goods within the supply chain. To solve the proposed model, a novel hybrid algorithm is introduced: the Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithm, or PSOSA, ensuring robust optimization under uncertainty and enhancing decision-making within the perishable goods supply chain. The research findings underscore the inadequacy of prevailing assumptions regarding the fixed lifespan of perishable products, commonly observed in the literature. By accounting for uncertainty in perishable goods’ lifespan, a more accurate representation of total producer costs is achieved, highlighting the misleading reduction of 25% observed when neglecting such uncertainty.

An order fulfilment location planning model for perishable goods supply chains using population density

The increased frequency of purchases and growing distances between the final distribution points of the perishable products and consumers are contributing to multiple handling, high intermediation, and a greater concentration of outlets selling perishables goods. These in turn have increased logistics costs, and inefficiencies in the supply chain. This study presents a modelling framework for locating perishable goods order fulfilment centers (OFC) near the consumer by using population density as a proxy for demand. The centrality and Borda count measures are used to identify optimal locations in perishable goods supply chain networks. We present a case study to demonstrate the applicability and efficacy of the proposed density-based spatial methodology.

A pricing and transshipment hybrid strategy for perishable product in two external scenarios for supply disruption

PurposeDifferent external supply scenarios faced by the retailers will affect their choice of strategy when supply is disrupted and becomes far less than demand, urgently. This study focuses on analyzing both demand and supply side response strategies to meet customer demand and reduce the impact of the shortage during supply disruptions.Design/methodology/approachAccording to the quantity of products that the external market can provide, the external supply scenarios were divided into sufficient-type external supply and learning-type external supply. A two-echelon perishable goods supply chain was analyzed, and three kinds of contingency strategy models for downstream retailers were investigated. First, in the sufficient external supply scenario, the optimal price and transshipment quantity to maximize retailer's profits is discussed. Second, in the scenario of learning-type external supply, this study analyzes the optimal decision in three mechanisms of the hybrid strategy and their application: price priority mechanism, quantity priority mechanism and price–quantity balance mechanism. Furthermore, the influence of penalty cost and supply on the priority orders of different mechanisms was studied.FindingsResults show that comparing the two pure strategies (pricing strategy and transshipment strategy)it was noted that the hybrid strategy produces the best results in sufficient-type external supply scenario. In the learning-type external supply scenario, a numerical study has shown the existence of three areas in case of penalty cost and supplier's capacity, and each areas has different priority orders of the three mechanisms. Under the situation of learning external supply, the retailer's optimal strategy is affected by parameters such as penalty cost and supply volume.Originality/valueThe main innovation of the work lies in the following: First; the external supply situation was divided into sufficiency type and learning type, which improves the external situation faced by retailers after the outbreak of emergencies, helps retailers understand the external situation, conforms to the actual situation and has certain practical application value. Second; in the context of learning external supply, there are three coping strategies for retailers, including: Price priority mechanism, Quantity priority mechanism and Pricing and transshipment balance mechanism. This will help retailers make strategic choices, make more scientific management decisions and improve the supply chain emergency management theory. Third; the demand side response was managed through the change of external supply during supply side recovery period and supply disruption. The proposed model enables managing and analyzing supply disruption efficiently and effectively via handling uncertainty by considering all aspects of decision-making process. The proposed model can be applied in various fields such as vegetable and fruit, fresh food, etc.

Blockchain-based traceability system adoption decision in the dual-channel perishable goods market under different pricing policies

The blockchain-based traceability system (BTS) can reduce product losses in the perishable goods market, which yields a loss-reduction effect, and offer authentic information, which triggers a premium effect. In a dual-channel perishable goods supply chain (DPGSC), including one supplier and retailer each, the supplier can operate the price of the direct channel, different or non-different from that of the traditional channel. To study the adoption of BTS in the supplier-led DPGSC, we employed a game-theoretical model to capture BTS adoption strategy under the differential and non-differential pricing policies and proposed an improved cost-sharing contract to boost the DPGSC performance. The results indicated that both the supplier and the retailer are willing to improve product quality, broaden the saleable region, and lower the production cost. The adoption of BTS mainly depends on the losses-reduction effect, premium effect, production cost, and tag cost, which is affected more by the premium effect than by the loss-reduction effect. Furthermore, their adoption is not always easier when the production cost is higher. Except for symmetric base demands, they benefit asynchronously from BTS. Synchronised adoptions can be realised only when the improved cost-sharing contract generates more profits and introduces excess momentum. Highlights Blockchain-based traceability system handles product losses and forged information Adoption decision-making processes under two different pricing policies are studied In the adoption process, the premium effect outweighs the loss-reduction effect Contract may introduce insufficient momentum, excess momentum, or new inefficiency Once excess momentum is formed, supply chain members' adoptions become synchronised

Multi-objective multi-echelon distribution planning for perishable goods supply chain: a case study

The growing concern of leading a healthy and balanced lifestyle has instigated the rise of the global consumption of fresh fruits and vegetables. However, the overall supply chain, particularly the product delivery system, is significantly hampered due to uncertain circumstances, such as a pandemic, natural disaster, and political strikes. Thus, better strategical decisions such as improved and optimised distribution planning have to be made to reduce this wastage and spoilage and ensure sustainability across its chain. Therefore, to ensure a sustainable supply chain architecture, this research proposes a tri-objective optimisation model for multi-echelon and multi-products aiming to lessen the annual supply chain cost, cold storage setup cost, and enhance the freshness of perishable by establishing a proper distribution channel. First, a mixed-integer linear programming model with three competing goals is proposed to solve the supply chain distribution network design problem. Then, to deal with the multi-criteria problem, a weighted sum method is considered. This was solved using CPLEX optimisation studio. A case study is considered to check the feasibility of the model with two common fruits of Bangladesh, i.e. guava and lemon. Finally, several cost-effective options and trade-offs between three factors are presented to aid the decision-making process. Highlights A unique flexible distribution planning model for multi-product fresh produce Allocating a new echelon, refrigerated DC between production and consumption zone Considering waste minimization and carbon emission to improve sustainability Determining the most preferred location of DCs from potential locations Establishing cold storages, considering perishable nature for developing countries

Impact of Bullwhip Effect in Quality and Waste in Perishable Supply Chain

The bullwhip effect results from inefficiencies in the supply chain; in perishable products, the inefficiencies are quality in the supply chain and product waste. We carried out a literature review to determine the causes of the bullwhip effect and the supply chain’s quality factors of this phenomenon’s perishable products. Update the demand, the level of deterioration of the product, and the number of intermediaries is the causes of the bullwhip effect most investigated. On the other hand, the product’s safety and the quality of the information are the quality factors of the chain of supplies of perishable products more researched. Future research should address the causes of human behavior that affect the bullwhip effect in the perishable goods supply chain.

Sustainable supply chain management for perishable products in emerging markets: An integrated location-inventory-routing model

The demand for perishable products in emerging markets has been increasing. However, the perishability of products brings tremendous challenges for firms to build a sustainable supply chain. In this paper, we propose an integrated model of location-inventory-routing for perishable products, considering the factors of carbon emissions and product freshness. First, the economic cost, carbon emission levels, and freshness of the perishable products are analyzed. Second, with the goals of achieving the lowest economic cost and carbon emissions and the highest product freshness, a multi-objective planning model is developed, and constraints are established based on the actual location-inventory-routing situation. Third, the YALMIP toolbox is used to solve the model, and the optimal solution to this complex multi-objective problem is obtained. Finally, the effectiveness and feasibility of the proposed method are verified by the case study, as well as the sensitivity vehicle speed to the results. It is found that the integrated model proposed in this paper is able to significantly improve the efficiency of perishable goods supply chain management from the perspective of global optimization, and vehicle speed is able to significantly affect economic costs and carbon emissions.

Optimal credit term, order quantity and selling price for perishable products when demand depends on selling price, expiration date, and credit period

The demand for perishable goods (e.g., baked goods, fruits, vegetables, meat, milk, and seafood) is influenced by product freshness which gradually declines over time and can be perceived by its expiration date. Also, selling price is an important factor on demand. Furthermore, most modern companies offer their products on various credit terms to increase sales. However, relatively little attention has been paid to the combined effects of selling price, expiration date and credit term affecting demand. In this paper, a three-echelon supplier-retailer-consumer supply chain for perishable goods is explored in which the retailer receives an upstream full trade credit from the supplier while granting a downstream partial trade credit to credit-risk customers, with demand as a multiplicative form of selling price, expiration date, and credit period. The proposed model includes numerous previous models as special cases. The optimal credit term, order size and selling price are derived simultaneously for the retailer to achieve maximum profit. Several numerical examples are conducted to gain managerial insights. For example, if the credit efficiency of demand increases, then the retailer shall offer a longer downstream credit period to raise sales volume, which in turn implies the retailer can raise a higher price, order a larger quantity, and gain a higher total profit. Conversely, an increase in portion of cash payment results in a lower demand rate. Hence, the retailer orders less quantity and earns less profit while decreasing price to stimulate sales. Finally, conclusions and future research directions are provided.

Designing a supply chain network for deteriorating inventory under preservation effort and trade credits

When designing a perishable goods supply chain network under trade credit arrangements, distribution companies must contend with deteriorating inventory and product preservation efforts to maximise profits. Key decisions include locating distribution centres (DCs), assigning retail stores to DCs, joint replenishment cycle time and investing in preservation technology. This paper addresses these factors from the position that as preservation effort increases, preservation technology cost increases and deterioration rate decreases. An algorithm based on piecewise nonlinear optimisation is provided for solving supply chain network design problems efficiently. In contrast to other studies that have used the approximation approach, the proposed approach solves the original problem accurately and efficiently. Numerical studies are conducted to demonstrate the solutions procedures and determine the effects of the parameters on decisions and profits. The results of this study and the proposed modelling approach are useful references for managerial decisions in designing a supply chain network the context of trade credit and inventory deterioration.

Designing supply contracts for perishable goods with two periods of shelf life

A critical feature of a perishable product is its age. When “old” units are on the shelf along with “young” units, a supplier who is designing a contract for a buyer must consider the product’s age. While numerous papers in the contracting literature have discussed channel coordination, none have studied the case in which the supplier needs to account for both old and young units. This article considers a supply chain for perishable goods with a two-period shelf life to address the aforementioned supplier’s problem. A two-level wholesale price contract, a two-level buy-back contract, and a buy-back contract with channel rebates are studied. The channel-coordinating conditions under each of these contracts are demonstrated. Although all three contracts can coordinate the channel, potential implementation issues with each of them are discussed and guidance for suppliers who want to design a contract when selling both old and young units is provided.

Dynamic ordering and pricing for a perishable goods supply chain

The paper studies the combined problem of pricing and ordering for a perishable product supply chain with one supplier and one retailer in a finite horizon. The lifetime of the product is two periods and demand in each period is random and price-sensitive. In each period, the supplier determines first a wholesale price and then the retailer decides an order quantity and retail prices. We show that the optimal pricing strategy for the non-fresh product depends only on its inventory, and the optimal pricing strategy and the optimal order quantity for the fresh product depend only on the wholesale price and they have a constant relation. Moreover, the game between the retailer and the supplier for finite horizon is equivalent to a one period game with only one order. Thus, the optimal policies are identical at each period. For the additive and multiplicative demands, we further obtain equations to compute the optimal strategies. All of above results are extended into the infinite horizon case and longer lifetime products. Finally, a numerical analysis is given.

Managing Perishables with Substitution: Inventory Issuance and Replenishment Heuristics

We consider a discrete-time supply chain for perishable goods having separate demand streams for items of different ages. For a good that has two periods of lifetime, we build a model that generalizes and/or subsumes many of the models in the literature and study the effectiveness of two intuitive heuristic (base-stock) replenishment policies combined with different substitution rules. For each replenishment policy, we identify sufficient conditions on cost parameters for a substitution rule to be economically superior to others under our base-stock replenishment policies. Our analysis shows that the replenishment policy almost universally advocated in the perishable inventory literature may lead to pathological behavior when used with issuance rules that pool inventory (via substitution) to satisfy multiple, age-differentiated demand streams. Furthermore, we find that system behavior is typically more predictable, and potentially less costly, under a policy long-discarded in the literature that ignores the inventory of aged items, ordering a constant amount each period. Thus the benefit of pooling inventory for substitutable, perishable products depends critically on the replenishment policy used.