Limited Inventory Research Articles

Optimal Production Scheduling in the Dairy Industries

This work presents the application of a Mixed-Integer Linear Programming (MILP) model that was previously developed in our group for the lot-sizing and production scheduling problem in a real-life industry. In particular, the case of yoghurt production, a representative food process, in a large-scale dairy facility from Greece is studied in detail. The model takes into account all constraints typically met in production scheduling (inventory limitations, material balances, equipment capacity, etc.) having as major objective the minimization of cost. New information regarding new orders, order modifications and/or cancellations and deviations of actual to planned production is considered by utilizing a rolling horizon algorithm. The suggested solution strategy has been successfully integrated with the industrial partner’s system to facilitate the decision-making process for the production scheduling of the facility.

Assessment of urban flood susceptibility using semi-supervised machine learning model

In order to identify flood-prone areas with limited flood inventories, a semi-supervised machine learning model—the weakly labeled support vector machine (WELLSVM)—is used to assess urban flood susceptibility in this study. A spatial database is collected from metropolitan areas in Beijing, including flood inventories from 2004 to 2014 and nine metrological, geographical, and anthropogenic explanatory factors. Urban flood susceptibility is mapped and compared using logistic regression, artificial neural networks, and a support vector machine. Model performances are evaluated using four evaluation indices (accuracy, precision, recall, and F-score) as well as the receiver operating characteristic curve. The results show that WELLSVM can better utilize the spatial information (unlabeled data), and it outperforms all comparison models. The high-quality WELLSVM flood susceptibility map is thus applicable to efficient urban flood management.

Value stream mapping and system dynamics integration for manufacturing line modelling and analysis

Companies have to meet clients' requirements with regard to product quality and delivery time. In order to survive and have possibilities to develop, companies should do it at minimal cost. The lean manufacturing implementation approach together with lean tools, such as value stream mapping (VSM), is an efficient way for waste identification and elimination. However, since VSM enables only a static analysis of a manufacturing system, the authors present in this paper how the integration of VSM with a system dynamics analysis (SDA) may increase the possibilities for waste identification and elimination. At first, the methodology of extended VSM is described. Then, an extended value stream map (VSMap) is developed and a system dynamics model (SDM) for a case study from the automotive industry is presented. Next, simulations in Vensim software are performed considering the inventory limitations and disturbances such as delivery delays, machine failures and nonconformities. The results are related to inventory levels, a number of manufactured products and work stand load. The article proves that the proposed extended VSM may be used as the only source of data for the construction of a manufacturing line computer model. The paper also argues that the integration of VSM and SD allows not only to identify and eliminate waste, but also to understand the impact of the identified problems on WIP and the production volume.

Dynamic Pricing of Fashionable Products with C2C Marketplaces and Strategic Consumers

This paper studies the influence of C2C resale marketplaces on pricing decisions and revenue performance of a capacitated seller selling high-tech or fashion products. We consider a monopolist seller sells fashionable products to consumers over two periods. Consumers who purchased early can resell their used units in online marketplaces later if their realized valuations turn out to be low. Additionally, consumers can strategically choose when (the first period or the second period) and where (from the seller or from the marketplace) to purchase. We characterize strategic consumers' purchasing equilibrium, the equilibrium market-clearing price for the resale marketplace, and the seller's optimal pricing decisions. First, we demonstrate that when the seller is capacitated with limited inventory, the resale marketplace will always benefit the seller. The seller can further strengthen the benefit by designing products with superior quality, a long-lasting valuation, and through cultivating early markets. Second, we show that with high initial inventory, the seller benefits from the marketplace only when the first-period market size is comparatively smaller than that of the second period. Under such a scenario, the seller is better off designing fashion-oriented products with acceptable quality and attracting more non-tech-savvy consumers who typically arrive and purchase late. Finally, we show that a Buy-Back Program, through which consumers can sell their used units back to the primary seller at a discounted price, can influence consumers’ purchasing behavior and improve the seller's revenue performance.

Food pantries as partners in population health: Assessing organizational and personnel readiness for delivering nutrition-focused charitable food assistance

ABSTRACTFood pantries serve populations with high rates of chronic disease and thus may be ideal settings for community-based health promotion programs. This study aimed to describe the readiness of food pantry organizations (n = 69) and their personnel (n = 129) to engage in nutrition-focused food pantry services, including nutrition education and the application of dietary guidelines for disease prevention and management as components of existing food assistance programs. Among survey respondents, few personnel reported asking clients about chronic disease diagnoses or providing clients with nutrition education, and over half reported lower confidence in performing these activities. Yet, the majority were interested in training to address client health needs. However, organizational capacity is currently restricted by lack of nutrition policies and limited healthy food inventory, including fruits and vegetables. To address the nutritional needs of clients, food pantries may benefit from in-person training and additional resources to obtain and distribute healthier foods.

Genomic Analysis of Picochlorum Species Reveals How Microalgae May Adapt to Variable Environments.

Understanding how microalgae adapt to rapidly changing environments is not only important to science but can help clarify the potential impact of climate change on the biology of primary producers. We sequenced and analyzed the nuclear genome of multiple Picochlorum isolates (Chlorophyta) to elucidate strategies of environmental adaptation. It was previously found that coordinated gene regulation is involved in adaptation to salinity stress, and here we show that gene gain and loss also play key roles in adaptation. We determined the extent of horizontal gene transfer (HGT) from prokaryotes and their role in the origin of novel functions in the Picochlorum clade. HGT is an ongoing and dynamic process in this algal clade with adaptation being driven by transfer, divergence, and loss. One HGT candidate that is differentially expressed under salinity stress is indolepyruvate decarboxylase that is involved in the production of a plant auxin that mediates bacteria-diatom symbiotic interactions. Large differences in levels of heterozygosity were found in diploid haplotypes among Picochlorum isolates. Biallelic divergence was pronounced in P. oklahomensis (salt plains environment) when compared with its closely related sister taxon Picochlorum SENEW3 (brackish water environment), suggesting a role of diverged alleles in response to environmental stress. Our results elucidate how microbial eukaryotes with limited gene inventories expand habitat range from mesophilic to halophilic through allelic diversity, and with minor but important contributions made by HGT. We also explore how the nature and quality of genome data may impact inference of nuclear ploidy.

Unreliable and Difficult-to-Access Food for Those in Need: A Qualitative and Quantitative Study of Urban Food Pantries.

For individuals who are food insecure, food pantries can be a vital resource to improve access to adequate food. Access to adequate food may be conceptualized within five dimensions: availability (item variety), accessibility (e.g., hours of operation), accommodation (e.g., cultural sensitivity), affordability (costs, monetary or otherwise), and acceptability (e.g., as related to quality). This study examined the five dimensions of access in a convenience sample of 50 food pantries in the Bronx, NY. The design was cross-sectional. Qualitative data included researcher observations and field notes from unstructured interviews with pantry workers. Quantitative data included frequencies for aspects of food access, organized by the five access dimensions. Inductive analysis of quantitative and qualitative data revealed three main inter-related findings: (1) Pantries were not reliably open: only 50% of pantries were open during hours listed in an online directory (several had had prolonged or indefinite closures); (2) Even when pantries were open, all five access dimensions showed deficiencies (e.g., limited inventory, few hours, pre-selected handouts without consideration of preferences, opportunity costs, and inferior-quality items); (3) Open pantries frequently had insufficient food supply to meet client demand. To deal with mismatch between supply and demand, pantries developed rules for food provision. Rules could break down in cases of pantries receiving food deliveries, leading to workarounds, and in cases of compelling client need, leading to exceptions. Adherence to rules, versus implementation of workarounds and/or exceptions, was worker- and situation-dependent and, thus, unpredictable. Overall, pantry food provision was unreliable. Future research should explore clients' perception of pantry access considering multiple access dimensions. Future research should also investigate drivers of mismatched supply and demand to create more predictable, reliable, and adequate food provision.

Unlocking biodiversity and conservation studies in high-diversity environments using environmental DNA (eDNA): A test with Guianese freshwater fishes.

Determining the species compositions of local assemblages is a prerequisite to understanding how anthropogenic disturbances affect biodiversity. However, biodiversity measurements often remain incomplete due to the limited efficiency of sampling methods. This is particularly true in freshwater tropical environments that host rich fish assemblages, for which assessments are uncertain and often rely on destructive methods. Developing an efficient and nondestructive method to assess biodiversity in tropical freshwaters is highly important. In this study, we tested the efficiency of environmental DNA (eDNA) metabarcoding to assess the fish diversity of 39 Guianese sites. We compared the diversity and composition of assemblages obtained using traditional and metabarcoding methods. More than 7,000 individual fish belonging to 203 Guianese fish species were collected by traditional sampling methods, and ~17 million reads were produced by metabarcoding, among which ~8 million reads were assigned to 148 fish taxonomic units, including 132 fish species. The two methods detected a similar number of species at each site, but the species identities partially matched. The assemblage compositions from the different drainage basins were better discriminated using metabarcoding, revealing that while traditional methods provide a more complete but spatially limited inventory of fish assemblages, metabarcoding provides a more partial but spatially extensive inventory. eDNA metabarcoding can therefore be used for rapid and large-scale biodiversity assessments, while at a local scale, the two approaches are complementary and enable an understanding of realistic fish biodiversity.

Intensifying heat transfer in Fischer-Tropsch tubular reactors through the adoption of conductive packed foams

The low-temperature Fischer-Tropsch synthesis is a strongly exothermic process wherein the temperature control is a crucial issue. In this work, we demonstrate experimentally for the first time the adoption of a Fischer-Tropsch tubular reactor (2.78 cm I.D.) loaded with a highly conductive open-cell aluminum foam packed with catalyst microspheres to enhance heat exchange. Accordingly, the performances of a highly active Co/Pt/Al2O3 catalyst packed into the metallic structure are assessed at industrially relevant operating conditions and compared with those obtained in a conventional randomly packed fixed-bed reactor. The structured catalyst reaches outstanding performances (duties in excess of 1300 kW/m3 with CO conversions >65%) with a remarkable temperature control. Almost flat axial temperature profiles are measured along the catalytic bed even under the most severe process conditions, showing the excellent ability of the “highly conductive packed-foam reactor” concept to manage the strong exothermicity of the reaction. In contrast, when the same experiment is carried out over the same Co/Pt/Al2O3 catalyst just randomly packed in the reactor, an abrupt increase of the catalyst temperature occurs already at low temperature, eventually leading to thermal runaway. The results herein collected prove the potential of conductive metal foams as enhanced reactor internals for the intensification of strongly exothermic processes in nonadiabatic tubular reactors. Furthermore, the “packed-foam” configuration also demonstrates the possibility to overcome the inherently limited catalyst inventory of the washcoated conductive structured reactors proposed so far, thus boosting the productivity per reactor volume.

Unexpected conservation of the RNA splicing apparatus in the highly streamlined genome of Galdieria sulphuraria

BackgroundGenome reduction in intracellular pathogens and endosymbionts is usually compensated by reliance on the host for energy and nutrients. Free-living taxa with reduced genomes must however evolve strategies for generating functional diversity to support their independent lifestyles. An emerging model for the latter case is the Rhodophyta (red algae) that comprises an ecologically widely distributed, species-rich phylum. Red algae have undergone multiple phases of significant genome reduction, including extremophilic unicellular taxa with limited nuclear gene inventories that must cope with hot, highly acidic environments.ResultsUsing genomic data from eight red algal lineages, we identified 155 spliceosomal machinery (SM)-associated genes that were putatively present in the red algal common ancestor. This core SM gene set is most highly conserved in Galdieria species (150 SM genes) and underwent differing levels of gene loss in other examined red algae (53-145 SM genes). Surprisingly, the high SM conservation in Galdieria sulphuraria coincides with the enrichment of spliceosomal introns in this species (2 introns/gene) in comparison to other red algae (< 0.34 introns/gene). Spliceosomal introns in G. sulphuraria undergo alternatively splicing, including many that are differentially spliced upon changes in culture temperature.ConclusionsOur work reveals the unique nature of G. sulphuraria among red algae with respect to the conservation of the spliceosomal machinery and introns. We discuss the possible implications of these findings in the highly streamlined genome of this free-living eukaryote.

VSM BASED SYSTEM DYNAMICS ANALYSIS TO DETERMINE MANUFACTURING PROCESSES PERFORMANCE INDICATORS

minimize costs, companies implement lean manufacturing concept and lean tools such as the value stream mapping (VSM) to identify and then eliminate waste. VSM allows a static analysis therefore the authors of this work propose integration of VSM with system dynamics analysis (SDA). Hence, first in the work an extended VSM is presented. Then, on the base of a developed extended value stream map (VSMap) for an automotive industry case study, an adequate simulation model was created. For simulations Vensim software was used. The case study of manufacturing line dynamics were analyzed. In the analysis, the inventory limitations were taken into consideration as well as disturbances such as machine failures and nonconformities. As a result, the dynamics of inventory levels and work stands load were presented.

Real-time teaming of multiple reconfigurable manufacturing systems

Personalized production poses new challenges on reconfigurable manufacturing systems due to a dramatic increase in the variety and stochasticity of the manufacturing demand. This paper proposes a connected autonomous reconfigurable manufacturing system with a decentralized management of individual autonomous lines that can be reconfigured for diverse manufacturing tasks via manufacturing modules. We present a mathematical approach for distributing the stochastic demands and exchanging machines or modules among lines (which are groups of machines) as a bidding process, and for adaptively configuring these lines and machines for the resulting shared demand under a limited inventory of configurable components.

Modeling landslide susceptibility in data-scarce environments using optimized data mining and statistical methods

This study evaluated the generalizability of five models to select a suitable approach for landslide susceptibility modeling in data-scarce environments. In total, 418 landslide inventories and 18 landslide conditioning factors were analyzed. Multicollinearity and factor optimization were investigated before data modeling, and two experiments were then conducted. In each experiment, five susceptibility maps were produced based on support vector machine (SVM), random forest (RF), weight-of-evidence (WoE), ridge regression (Rid_R), and robust regression (RR) models. The highest accuracy (AUC=0.85) was achieved with the SVM model when either the full or limited landslide inventories were used. Furthermore, the RF and WoE models were severely affected when less landslide samples were used for training. The other models were affected slightly when the training samples were limited.

Optimal Rebate Strategies Under Dynamic Pricing

Instant discounts and mail-in rebates are two common pricing tools in retail, but they are not simple substitutes. On the one hand, consumers discount the face value of a mail-in rebate, making it less effective than an instant discount in inducing consumers’ purchase. On the other hand, a portion of consumers with mail-in rebates fail to redeem them, resulting in savings for the retailer. We study how retailers, under pressure to move inventory, should use these two pricing tools to maximize revenue by determining the optimal use of mail-in rebates together with dynamic pricing of limited inventory. In a base model that allows frequent adjustment of product price and rebate face value, the optimal policy takes the form of “discount only,” “rebate only,” or a combination of the two. For useful heuristics with infrequent policy adjustment, we analyze the deterministic approximation of the base model. Interestingly, the deterministic solution splits the selling season into two segments, and it suggests using different pricing-rebate policies in each segment. Finally, we study a scenario in which the retailer has only one opportunity to introduce a static rebate, and we find that for any inventory level there is a cutoff time before which rebates should not be used. Our numerical studies show that such an optimal one-time static rebate policy performs well compared with the optimal revenue in the benchmark model. The online appendix is available at https://doi.org/10.1287/opre.2017.1642 .

Exportation of dissolved (inorganic and organic) and particulate carbon from mangroves and its implication to the carbon budget in the Indian Sundarbans

Mangroves are known for exchanging organic and inorganic carbon with estuaries and oceans but studies that have estimated their contribution to the global budget are limited to a few mangrove ecosystems which exclude world's largest the Sundarbans. Here, we worked in the Indian Sundarbans and in the Hooghly river/estuary in May (pre-monsoon) and December (post-monsoon), 2014. Aims were, i) to quantify the riverine export of particulate organic carbon (POC) and dissolved organic and inorganic carbon (DOC, DIC)) of the Hooghly into the Bay of Bengal (BoB), ii) to estimate the C export (DOC, DIC, POC) from the Sundarbans into the BoB by using a simple mixing model, as well as iii) to revise the existing C budget constructed for the mangroves. The riverine exports of POC, DOC and DIC account for 0.07TgCyr−1, 0.34TgCyr−1 and 4.14TgCyr−1, respectively, and were largest during the monsoon period. Results revealed that mangrove plant derived organic matter and its subsequent degradation is the primary source of DIC and DOC in the Hooghly estuary whereas POC is linked to soil erosion. Mangroves are identified as a major source of carbon (POC, DOC, DIC) transported from the Sundarbans into the BoB, with export rates of 0.58 TgCyr−1, 3.03TgCyr−1, and 3.69TgCyr−1 respectively, altogether amounting to 7.3TgCyr−1. This C export from the Indian Sundarbans exceeds the ‘missing C’ of the previous budget, thus necessitating further research to finally resolve the mangrove C budget. However, these first baseline data on C exports from the world's largest deltaic mangrove improves limited global data inventory and signifies the need of acquiring more data from different mangrove settings to reduce uncertainties.

Product Portfolio Management with Production Flexibility in Agribusiness

The acquisition of production flexibility is a well-documented strategy pursued by many firms to counteract certain operational constraints. However, these flexibilities can increase the complexity of a production system and the difficulties in managing increased complexity may hinder exploiting the full benefit of flexibility. In this paper, we consider one such flexibility paradox at an agribusiness firm for an annual $800 million production decision: The firm produces a number of products (hybrid seeds) using limited inventories of several raw materials (parent seeds) and a production process that is subject to random variations. To handle the raw material availability constraint and to partially mitigate the supply risk, the firm invests in a costly second production in South America that can be used if the yield in the first production in North America is low. We solve this joint problem of raw material allocation and sequential production by reformulating it as a tractable simultaneous optimization problem. This tractable reformulation provides an exact solution in practical time durations for large assortments of products. We also establish that when profit margins are sufficiently high, sequential production has less cost, on average, than single production. The solution developed is in use at the firm and has led to an estimated increase in profit by 2%–3% annually.

Price competition under linear demand and finite inventories: Contraction and approximate equilibria

We consider a multi-period price competition among multiple firms with limited inventories of substitutable products, and study two types of equilibrium: with and without recourse. Under a linear demand model, we show that an equilibrium without recourse uniquely exists. In contrast, we show an equilibrium with recourse need not exist, nor be unique. In a low-influence regime, using the equilibrium without recourse, we construct an approximate equilibrium with recourse with the same equilibrium price trajectory.

Is Ignorance Bliss? A Note on Dynamic Pricing with Demand Learning

In this paper, we present an interesting observation that seems at odds with the common belief that Bayesian learning should do better than no learning. Specifically, in a dynamic pricing problem with limited inventory for sale, we show that the optimal revenue of a learning system can be lower than that of a no-learning system, suggesting that ignorance is bliss. Our subsequent investigation into a two-state model reveals that the superior performance of the no-learning system is actually an exaggeration due to an overly optimistic demand belief resulted from its ignoring of past demand observations. We also show that this insight reverses as the demand environment becomes more cyclic. We further verify the robustness of the insight under a continuous-state model. Our findings shed light on the importance of inventory assumption in dynamic pricing problems - whether inventory is ample or limited can lead to drastically different insights about demand learning.

Dynamic Recommendation at Checkout under Inventory Constraint

This work is motivated by a new checkout recommendation system at Walmart's online grocery, which offers a customer an assortment of up to 8 items that can be added to an existing order, at potentially discounted prices. We formalize this as an online assortment planning problem under limited inventory, with customer types defined by the items initially selected in the order. Multiple item prices, combined with customer withdrawal when their initially selected items stock out, pose additional challenges for the development of an online policy. We overcome these challenges by introducing the notion of an inventory protection level in expectation, and presenting an algorithm with bounded competitive ratio when the arrival sequence is chosen adversarially. We further conduct numerical experiments which compare the performance of our algorithm with several existing benchmarks.

Immunological complications of blood transfusions

Most adverse blood transfusion (BT) events are immune-mediated and in the majority of severe reactions antibodies can be identified as causal factors. Alloimmunization not only causes symptomatic reactions, transfused cells can also be (silently) destroyed. Immunization by BT can contribute to hemolytic disease of the newborn as well as to allograft rejection after transplantation. Reversely, pregnancy and transplantation may evoke immunity hampering transfusion therapy. Besides causing mortality and morbidity, alloimmunization has a huge economic impact. Transfusion reactions prolong hospital stay, require diagnostic tests and complex donor selection procedures and create the need for typed donor registries. In the 1970s, Opeltz and colleagues described that pre-transplantation BT impaired rejection of renal transplants. Leukocytes were essential for this immunosuppressive BT effect that raised concern about negative effects on cancer growth and resistance against infections. Studies on the mechanism were however preliminary abandoned when calcineurin inhibitors for prevention of graft rejection became available and since all blood products underwent leukoreduction in most countries as precautionary measure against transmission of variant Creutzfeldt-Jacob disease. Whether current leukoreduced BT are immunosuppressive and for which patients or circumstances this may contribute to worse outcome, is unknown. The last decades of the previous century, leukoreduction of cellular blood products for leukemia patients significantly reduced the incidence of immunological platelet transfusion refractoriness. The first decade of this century the avoidance of plasma- and platelet-products from females, that may contain donor-derived leukocyte antibodies, decreased transfusion related acute lung injury (TRALI) by more than 30%. These were major achievements. Challenge for the near future is to further reduce alloimmunization in particular against red blood cells (RBC) as a cause of severe hemolytic transfusion reactions and problems to find compatible donors. This can be achieved by extended matching. Inventory limitations prevent to match all BT for clinically relevant RBC antigens. A (European-wide) registration of clinical and genetic risk factors associated with alloimmunization could support effective use of matched blood products.