Academic literature on the topic 'Stocking programming'

Small property size is often cited as one of the major causes of rangeland degradation in Australia. However, there is some conjecture as to the importance of this effect and the process by which small property sizes lead to rangeland degradation. Relatively little empirical analysis of these issues has been undertaken, especially in a dynamic context which is all important in the case of rangeland degradation. Regression and dynamic programming techniques are employed in this study to investigate and measure the impact of property sizes on the use and state of one of Australia's most important rangelands, the Queensland mulga rangeland. Regression analysis of cross sectional data reveals significant correlations between property size, stocking rate and degradation. These correlations are confirmed in a normative stochastic dynamic programming model which demonstrates that it is economically optimal for graziers managing smaller properties to adopt higher stocking rates. For these graziers, the longterm costs of land degradation are exceeded by short-term financial benefits of heavier stocking. Thus government policy aimed at arresting the serious degradation occurring in the mulga rangelands should focus on measures to facilitate property build-up..

In the fresh supermarket, due to the particularity of fresh goods, the fresh-keeping time of vegetable goods is relatively short, generally the wholesale goods of the same day need to be sold on the same day, if the day is not sold, it will produce waste phenomenon. Therefore, fresh supermarkets generally choose to price and replenish goods every day according to their experience and sales status. By establishing the relevant mathematical model, this paper gives the replenishment and pricing decision of vegetable commodities after the supermarket optimization, so as to maximize the profit of the supermarket. First, the box chart is used to pre-process the data, and then the distribution law of the sales volume of each vegetable category and single product over time is analyzed by data analysis and visualization technology. Then the Pearson correlation coefficient of the sales volume of each vegetable category and each single product is obtained by heat map analysis, and the correlation relationship between them is inferred. Then, by calculating the average daily sales pricing of various vegetable varieties as the cost plus pricing of dishes, using linear function and logarithmic function to fit the sales volume and sales price of each vegetable category to get the functional relationship between the two. Finally, ARIMA model is used to predict the wholesale price of each dish within seven days, and then the equation model is established. Finally, SLSQP method is used to predict the total amount of replenishment and pricing strategy of six vegetable categories in the next week.

Dropshipping or dropship is a form of trade where resellers or retailers make sales without stocking goods. A website is needed to facilitate suppliers in finding a dropshipper. Website creation needs programming languages, such as PHP and MySQL as the DBMS. However, a model is required to create a software. One of the software development models is Waterfall. It is a sequential software development model that ranges from analysis to maintenance stages.

This study aims to help fresh produce superstores develop vegetable replenishment and pricing strategies to maximize their benefits. By analyzing historical sales records and customer demand, the study used an ARIMA model to predict future demand and a planning model to optimize superstore revenues. The study also analyzed the sales data of 6 major categories and 246 individual types of vegetables and found that flower and leafy vegetables were the most popular in the market. By performing Spearman correlation analysis on the sales volume data, the study obtained the two pairs of vegetable categories with the highest degree of correlation. In addition, a positive correlation between sales volume and total price was fitted by linear regression and converted to a negative correlation between cost-plus pricing and sales volume. Finally, past costs, damage rates, price factors, and demand were taken into account to optimize each day's data individually to maximize the superstore's revenue, where the maximum profit on the first day was $1,520.6.

Abstract This paper describes a computer program, REDPTHIN, that permits the development of optimal thinning schedules for red pine plantations in the Lake States. The optimal schedules maximize total cubic foot volume production for any initial stand condition of age, site, and basal area stocking. These optimal schedules are derived via a special dynamic programming algorithm that the author developed. User specified thinning schedules can be simulated. Optimal biological rotation age and mean annual increment can be derived from the output table. North. J. Appl. For. 12(1):43-48.

Development of a model of warm and stylish women's stockings with a jacquard pattern, suitable for mass production. Methodology. To achieve this goal, a review of patent and technical іnformation on the manufacture of hosiery with jacquard patterns was realized. Autodesk AutoCAD software is used to increase the effi ciency of product design. Findings. The study developed a collection of women's stockings with animal ornaments and patterns for making the same. A pattern simulating the color of a zebra's fur was chosen for experimental production.A two-color double bed jacquard stockings collection is designed. The production of this knit does not involve the knitting density changes. Correspondence of the stocking surface geometry to the measurements of a person’s leg can be provided by increasing or decreasing working needles. The latter cannot be realized on specialized circular knitting equipment for hosiery production. The models of the collection can be made on fl at knitting machines accord ing to the patterns. An experimental model is made of half-woolen yarn on a semi-industrial fl at knitting machine Brother KH-965i. The linker Hague D280E has been used for the stocking’s parts sewing. A parametric pattern of the unfolded product in Autodesk AutoCAD has been created. To adjust the pattern to the desired size, a customer has to enter the measurements and the boundary will be redrawn automatically. An application in the Autolisp programming language has been developed to automatically calculate the knitting program (increase and decrease the number of working needles). Entering course and wale spacing values of the sample structure in the program allows the automatically calculating the required number of working needles in each part of the product.Practical value. The technology of making women’s hosiery with design patterns on the basis of double jacquard knits on fl at-bed knitting machines has been develope d. Such products can be made both on modern fl at knitting machines with computer control, such as, for example, automated equipment of the Stoll or Shima Seiki brands and on semi-industrial knitting machines, such as Brother, Selver Red and others.

For retailing systems, arranging the perishable products has always been a challenge. Although more profit is made when products are sold with a FIFO policy, now customers taste in a competitive market which requires new products to be offered to them has changed the game. This paper considers a hybrid of FIFO-LIFO strategies for controlling a retailer's stock and its impact on the profits of the vendor managed inventory contracts. The problem is formulated as a multi-period, multi-store integer programming model which aims to maximize the total profit. The proposed model considers different selling prices and different holding costs for perishable products according to their remaining shelf life. A dynamic programming with a backward strategy is proposed to find the optimal order quantity for each store. The numerical experiments confirm the applicability and efficiency of the model illustrating impact of the crucial parameters of the model on the stocking policy.

L’objectif est de développer des modèles mathématiques et des algorithmes qui pourraient permettre de planifier efficacement les activités de production pour des systèmes de production de remanufacturation complexes, en présence d'incertitude. Nous considérons un système de remanufacturation comprenant trois échelons de traitement : le désassemblage, la remise en état et le réassemblage. Nous étudions le problème de la planification dans ce système sur un horizon de planification fini et discret, en présence d'incertitudes quant à la quantité et à la qualité des produits retournés, à la demande des clients et aux différents coûts de production. Nous proposons de modéliser ce problème d'optimisation combinatoire comme un programme entier stochastique à plusieurs étapes et d'utiliser un arbre de scénarios pour représenter l'évolution du processus stochastique dans le temps. Nous nous concentrons sur l'amélioration des performances des algorithmes génériques de branch-and-cut intégrés dans les solveurs de programmation mathématique grâce à l'utilisation d'approches de génération de coupes. Ensuite, afin de résoudre des instances plus grandes de notre problème, nous étudions un deuxième type d'approche de solution basée sur une décomposition du problème original en une série de sous-problèmes liés entre eux par des équations de programmation dynamique. Enfin, nous présentons un travail exploratoire en cours sur la gestion de stock stochastique multi-étapes prudente. Nous étudions ainsi plusieurs façons d'incorporer l'aversion au risque dans le problème (SULS) et montrons comment le SULS prudent peut être reformulé comme un programme linéaire à variables mixtes dans chaque cas
The main purpose of the work presented here is to develop mathematical models and algorithms that may enable industrial managers to efficiently plan production activities for complex remanufacturing production systems under uncertainty. In order to achieve this, we consider a remanufacturing system involving three processing echelons: disassembly, refurbishing and reasembly. We investigate the problem of planning remanufacturing activities in this system over a finite and discrete-time planning horizon when there are uncertainties on the quantity and quality of returned products, on the customers' demand, and on the various production costs. We propose to model this stochastic combinatorial optimization problem as a multi-stage stochastic integer program and to use a scenario tree to represent the evolution of the stochastic input process over time. We first focus on enhancing the performance of the generic branch-and-cut algorithms embedded in mathematical programming solvers through the use of cutting plane generation approaches. Second, in order to solve larger instances of our problem, we investigate a second kind of solution approach based on a decomposition of the original problem into a series of small sub-problems linked together by dynamic programming equations. Finally, we present an on-going exploratory work on risk-averse multi-stage stochastic lot-sizing. We thus study several ways of incorporating risk aversion in the multi-stage stochastic uncapacitated lot-sizing (SULS) problem and show how the risk-averse SULS can be reformulated as a mixed-integer linear program in each case

We consider a single-part, two-echelon supply chain problem for spare parts. The network consists of a single manufacturing plant, a set of service centers (SCs) and a set of customers. Both echelons keep spare parts using the base-stock replenishment policy. The plant behaves as an M/M/1 queueing system and has limited production and storage capacity. Demand faced by each SC follows an independent Poisson process. The problem is to determine optimal location-allocation and optimal base-stock levels at both echelons while satisfying the target service levels and customer preferences of SCs. We develop a mixed integer non-linear programming model and use cutting-plane method to optimize the inventory-location decisions. We present an exact solution procedure for the inventory stocking problem and demonstrate the limitations of using traditional inventory models like METRIC-like and Approximate in case of high utilization rates. We show the effectiveness of our proposed cutting-plane algorithm and provide important managerial insights for spare parts management.