Optimal pricing and lot-sizing decisions under Weibull distribution deterioration and trade credit policy

In this paper, we consider the problem of simultaneous determination of retail price and lot-size (RPLS) under the assumption that the supplier offers a fixed credit period to the retailer. It is assumed that the item in stock deteriorates over time at a rate that follows a two-parameter Weibull distribution and that the price-dependent demand is represented by a constant-price-elasticity function of retail price. The RPLS decision model is developed and solved analytically. Results are illustrated with the help of a base example. Computational results show that the supplier earns more profits when the credit period is greater than the replenishment cycle length. Sensitivity analysis of the solution to changes in the value of input parameters of the base example is also discussed

Optimal lot-sizing, pricing, and product intergenerational lifestyle decisions for the case of disruptive innovations in fashion

The objective of this dissertation is to determine production schedules, production quantities, selling prices, and new product introduction timing to fulfill deterministic price-dependent demand for a series of products in such a way as to maximize profit per period. In order to accomplish the above task, some main assumptions are made. First, it is assumed that the series of products being considered are associated with sequential non-disruptive innovations in technology as well as disruptive innovations in fashion. That is to say, the products represent subsequent generations in the same family of products in an industry that experiences repeated minor technological innovations and in which product success is due in part to fashionability (Fisher, 1997). Second, it is assumed that the planning horizon is sufficiently long and product lifecycles are sufficiently short that several generations of the product family are planned. Third, it is assumed that the producer is following a solo-product roll strategy (Billington, Lee, & Tang, 1998). This means that the inventory of one product iteration is exhausted at the same time that the next product iteration is introduced and ready for sale. Fourth, it is assumed that demand for each product iteration is governed by a modified version of the Bass (1969) diffusion model that incorporates price. Fifth, it is assumed that the various demand and cost characteristics being considered do not change from one product iteration to the next. Sixth, it is assumed that no backlog of demand is maintained and that any unmet demand is lost. Seventh, it is assumed that the manufacturer is a monopolist or at least the dominant member of a market that is made up of it and smaller competitors that are not large enough to affect the market in a meaningful way. The formulated profit maximization problem uses the Thomas (1970) model which in turn depends in its solution on theorems first presented by Wagner and Whitin (1958a). An extensive numerical study that aims at examining the sensitivity of the planned product lifecycle length and profit per period to changes in model parameters is performed using software developed especially for that purpose. The results of the analysis reveal that the above two measures are more sensitive to changes in market-oriented parameters than to changes in operations-oriented parameters. Managerial implications of the research findings are discussed

Optimal Inventory Policies for Weibull Deterioration under Trade Credit in Declining Market

The aim of this study is to develop mathematical model for Weibull deterioration of items in inventory in declining market when the supplier offers his retailers a credit period to settle the accounts against the dues. The computational steps are explored for a retailer to determine the optimal purchase units which minimize the total inventory cost per time unit. The numerical examples are given to demonstrate the retailer’s optimal decision. A sensitivity analysis is carried out to study the variations in the optimal solution.Weibull deterioration, trade credit, declining market

Pricing and inventory control policy for non-instantaneous deteriorating items with time- and price-dependent demand and partial backlogging

Determining the optimal inventory control and selling price for deteriorating items is of great significance. In this paper, a joint pricing and inventory control model for deteriorating items with price- and time-dependent demand rate and time-dependent deteriorating rate with partial backlogging is considered. The objective is to determine the optimal price, the replenishment time, and economic order quantity such that the total profit per unit time is maximized. After modeling the problem, an algorithm is proposed to solve the resulted problem. We also prove that the problem statement is concave function and the optimal solution is indeed global

Optimal Ordering and Trade Credit Policy for EOQ Model

Trade credit is the most prevailing economic phenomena used by the suppliers for encouraging the retailers to increase their ordering quantity. In this article, an attempt is made to derive a mathematical model to find optimal credit policy and hence ordering quantity to minimize the cost. Even though, credit period is offered by the supplier, both parties (supplier and retailer) sit together to agree upon the permissible credit for settlement of the accounts by the retailer. A numerical example is given to support the analytical arguments.Trade Credit, Optimal ordering quantity, Lot-size

Lot Sizing Optimisation for Stochastic Make-to-order Manufacturing

Lot sizing is pivotal to batch manufacturing, especially in stochastic environments. Although progress has been made in the field for some operational objectives, the optimised results are often rendered unrealistic because few studies have considered the overall business goal and the economic environment where businesses operate. This paper examines a stochastic lot sizing optimisation model for make-to-order manufacturing with a focus on the overall business goal—the maximisation of shareholder wealth. In addition to the economic objective, the effect of the economic environment is also incorporated into this model. Numerical experiments validate the importance of considering such economic and financial constraints and objectives, especially for firms with relatively high setup costs or being sensitive to lead times. The proposed model can assist the management in gaining insight into potential challenges and opportunities pertinent to the shareholder wealth.published_or_final_versio

Optimizing lot sizing model for perishable bread products using genetic algorithm

This research addresses order planning challenges related to perishable products, using bread products as a case study. The problem is how to effi­ci­ently manage the various bread products ordered by diverse customers, which requires distributors to determine the optimal number of products to order from suppliers. This study aims to formulate the problem as a lot-sizing model, considering various factors, including customer demand, in­ven­tory constraints, ordering capacity, return rate, and defect rate, to achieve a near or optimal solution, Therefore determining the optimal order quantity to reduce the total ordering cost becomes a challenge in this study. However, most lot sizing problems are combinatorial and difficult to solve. Thus, this study uses the Genetic Algorithm (GA) as the main method to solve the lot sizing model and determine the optimal number of bread products to order. With GA, experiments have been conducted by combining the values of population, crossover, mutation, and generation parameters to maximize the feasibility value that represents the minimal total cost. The results obtained from the application of GA demonstrate its effectiveness in generating near or optimal solutions while also showing fast computational performance. By utilizing GA, distributors can effectively minimize wastage arising from expired or perishable products while simultaneously meeting customer demand more efficiently. As such, this research makes a significant contri­bution to the development of more effective and intelligent decision-making strategies in the domain of perishable products in bread distribution.Penelitian ini berfokus untuk mengatasi tantangan perencanaan pemesanan yang berkaitan dengan produk yang mudah rusak, dengan menggunakan produk roti sebagai studi kasus. Permasalahan yang dihadapi adalah bagaimana mengelola berbagai produk roti yang dipesan oleh pelanggan yang beragam secara efisien, yang mengharuskan distributor untuk menentukan jumlah produk yang optimal untuk dipesan dari pemasok. Untuk mencapai solusi yang optimal, penelitian ini bertujuan untuk memformulasikan masalah tersebut sebagai model lot-sizing, dengan mempertimbangkan berbagai faktor, termasuk permintaan pelanggan, kendala persediaan, kapasitas pemesanan, tingkat pengembalian, dan tingkat cacat. Oleh karena itu, menentukan jumlah pemesanan yang optimal untuk mengurangi total biaya pemesanan menjadi tantangan dalam penelitian ini. Namun, sebagian besar masalah lot sizing bersifat kombinatorial dan sulit untuk dipecahkan, oleh karena itu, penelitian ini menggunakan Genetic Algorithm (GA) sebagai metode utama untuk menyelesaikan model lot sizing dan menentukan jumlah produk roti yang optimal untuk dipesan. Dengan GA, telah dilakukan percobaan dengan mengkombinasikan nilai parameter populasi, crossover, mutasi, dan generasi untuk memaksimalkan nilai kelayakan yang merepresentasikan total biaya yang minimal. Hasil yang diperoleh dari penerapan GA menunjukkan keefektifannya dalam menghasilkan solusi yang optimal, selain itu juga menunjukkan kinerja komputasi yang cepat. Dengan menggunakan GA, distributor dapat secara efektif meminimalkan pemborosan yang timbul akibat produk yang kadaluarsa atau mudah rusak, sekaligus memenuhi permintaan pelanggan dengan lebih efisien. Dengan demikian, penelitian ini memberikan kontribusi yang signifikan terhadap pengembangan strategi pengambilan keputusan yang lebih efektif dan cerdas dalam domain produk yang mudah rusak dalam distribusi roti

A Digital Twin Framework for Production Planning Optimization: Applications for Make-To-Order Manufacturers

In this dissertation, we develop a Digital Twin framework for manufacturing systems and apply it to various production planning and scheduling problems faced by Make-To-Order (MTO) firms. While this framework can be used to digitally represent a particular manufacturing environment with high fidelity, our focus is in using it to generate realistic settings to test production planning and scheduling algorithms in practice. These algorithms have traditionally been tested by either translating a practical situation into the necessary modeling constructs, without discussion of the assumptions and inaccuracies underlying this translation, or by generating random instances of the modeling constructs, without assessing the limitations in accurately representing production environments. The consequence has been a serious gap between theory advancement and industry practice. The major goal of this dissertation is to develop a framework that allows for practical testing, evaluation, and implementation of new approaches for seamless industry adoption. We develop this framework as a modular software package and emphasize the practicality and configurability of the framework, such that minimal modelling effort is required to apply the framework to a multitude of optimization problems and manufacturing systems. Throughout this dissertation, we emphasize the importance of the underlying scheduling problems which provide the basis for additional operational decision making. We focus on the computational evaluation and comparisons of various modeling choices within the developed frameworks, with the objective of identifying models which are both effective and computationally efficient. In Part 1 of this dissertation, we consider a class of Production Planning and Execution problems faced by job shop manufacturing systems. In Part 2 of this dissertation, we consider a class of scheduling problems faced by manufacturers whose production system is dominated by a single operation

Economic evaluation in decision models: a critical review and methodological propositions

International audienceDecision models of industrial management articles are often based on an economic criterion to find the proposed solution. They use economic parameters that are generally imported from the firm cost accounting system. When cost information is not adapted to the decision, the obtained solution of the model may be invalid. In this article, we deal with a critical literature review to report the methodological problems encountered in industrial management articles vis-à-vis the used costs. Finally we suggest methodological propositions to be kept in mind by authors when they are using costs in decision models