Total Purchasing Cost Research Articles

E3 Analysis for Crude and Vacuum Distillation System

AbstractCrude oil blending is a very common practice in petroleum refineries, where the main focus is to minimize the total purchase cost of crude oils under specified blending oil properties. Crude oil blending actually has significant impacts on energy consumption from heating furnaces during crude oil processing. Conceivably, furnace energy consumption from burning fuels such as natural gas, fuel oil, or propane causes huge amounts of CO2 emissions. In this paper, a methodology framework for crude oil blending and processing with simultaneous consideration of energy, emission, and economic profit (E3) is developed. It includes four stages of work: steady‐state modeling, heating energy consumption calculation, emission model development, and economic evaluation. With Aspen HYSYS simulation, the developed methodology provides a quantitative support for refinery to identify an optimal E3 operating strategy. A case study is implemented to demonstrate the efficacy of this methodology.

The impact of order allocation decision on supply chain benefits under multiple suppliers

Increasing competitive pressures, market globalization, and shortened product life cycles are forcing firms to develop supply chains that can quickly respond to customer needs. How to manage demand instability as well as controlling well makes a great impact on order allocation decisions, whereas it plays an important role in minimizing total purchasing costs, while maintaining a specified service level. The objective of this article is to explore how order allocation decisions influence a supply chain. A simulation-based system structure is therefore proposed for regular/urgent orders, and factors under consideration include cost, quality, delivery date, service quality, order fill rates, production capacity, and current order quantities simultaneously. Multiple concerns in this article include total turnover, purchasing costs, back order costs, transportation costs, and order waiting costs. Finally, its effectiveness in terms of the service level and the company's total purchasing cost is examined by a numerical example.

A soft time-windowed mechanism for vendor selection model

This paper presents a vendor selection model for buyers practicing Just-in-time management strategy. Five vendor evaluation criteria including quality, delivery, net price, geographical location, and production capacity are utilized for the selection of vendors and determination of associated purchasing quantities. A soft time window mechanism is incorporated to allow purchased parts been delivered within a grace period of time with a specified penalty function. A mixed-integer programming model is developed for this vendor selection problem. The proposed model encourages the buyer to select vendors capable of providing quality in-time products which will minimize the total cost of purchasing, quality, transportation, and penalty charge for violating the delivery time window. An illustrative example is given to demonstrate the implementation of the time-window model.

Hazardous waste reduction from mixed acid titanium etching

This paper presents the findings of a technical study performed by the New York State Pollution Prevention Institute at Rochester Institute of Technology to evaluate process modifications that would reduce hazardous waste generated from the manufacture of titanium alloy turbine blades. This study focused on the acid etch process step in which titanium alloy turbine blades are immersed in a mixed nitric and hydrofluoric acid solution to chemically mill the blades; which is one of a sequence of finishing steps. The spent acid is a hazardous waste that is sent off-site for disposal. A pollution prevention approach identified several process and operational improvements that would significantly reduce the amount of hazardous acid waste generated. Implementation of process improvements identified in this study resulted in reducing the quantity of hazardous waste generated from 502 tons/year in the Baseline year to less than 210 tons/year in Year 2, thereby resulting in a cost savings of nearly 43% per year. Full implementation of the study recommendations are expected to reduce the hazardous waste quantity to 71 tons/year, thereby achieving a cost savings of nearly 70% due to an 86% reduction in waste generation and a 66% reduction of total acid purchase and disposal costs.

Consumer Reactions to Unobserved Changes in Price Schedules

Economic theory presumes that individuals respond to true marginal prices when deciding on the amount of goods and services they buy and many other economic decisions. However, learning about these marginal prices is often costly in terms of search time, cognitive effort or monetary outlays. This is likely to be true of price changes in subscription plans. Consumers may therefore opt to be satisfied with only an approximate knowledge of the relevant marginal prices. This paper presents an experiment that studies repeated consumer purchase and price information updating and acquisition decisions when parameters of the price schedule are serially correlated but unknown. Subjects have an option to acquire the pricing information at a cost, or otherwise just update their beliefs based on the observation of the total cost of purchase. We find the following: (1) conditional on information acquisition decisions, the model of Bayesian updating provides a good approximation for revealed mean beliefs about the per-unit price held by subjects who appear to understand the experiment and/or report their expected cost of purchase accurately; it is not a good approximation for other subjects; (2) the demand for information decreases with the cost of information, as expected; (3) controlling for Bayesian beliefs and cost of information, the demand for information does not vary with the length of the remaining time horizon in which the information can be used, contrary to the theoretical prediction; (4) large positive surprises in the cost of purchase in the most recent period increase information demand, whereas negative surprises decrease it, relative to the no-surprise baseline, which is contrary to the theoretical prediction.

An Integrated Multi-Objective Decision Model under Considering Stochastic Demand, Price Breaks and Disruption Risk for Order Allocation in a Multiple-Supplier Environment

The objective of this article is to study the order allocation problems in a stochastic supply chain. This supply chain consists of a company that can order raw materials from multiple suppliers. At any time of a supply order, decisions have to be made by the company concerning the respective supplier order quantities and price breaks, so that the total purchasing cost and disruption risk cost are minimized, while maintaining a specified service level and quality. For this purpose, we have developed an integrated multi-objective decision model under random constraint to supply order allocation.

A decision support system for a purchasing model using an integration of MCDM and linear programming

In today's competitive global business environment, successful enterprises depend on quick and accurate decision making. In addition to a quick response, cost reduction is also a key issue if an enterprise strives to maintain its capability for competitiveness. The costs of raw materials and components might account for upwards of 70% of a product. In such circumstances, the purchasing department plays a key role in cost reduction, and acts an important link between the internal and external aff airs of the company. In this study, we developed a novel concept of an intelligent support system for purchasing systems (IDSS-PS) which includes an integration of Analytic Network Process (ANP) and linear programming. Through IDSS-PS, decision makers can normally get quantitative preference from suppliers and minimize the total purchasing cost.

Supplier selection and purchase problem with fixed cost and constrained order quantities under stochastic demand

This paper addresses a supplier selection and purchase problem under stochastic demand. In particular, a buyer firm (manufacturer or retailer) wants to procure a product from a group of potential suppliers, which may quote different prices and have restriction on minimum and maximum order sizes, to satisfy the uncertain demand. In addition to holding and shortage costs, a fixed cost is incurred for the buyer when a potential supplier is selected. The objective is to select suppliers and to allocate the ordering quantity properly among the selected suppliers to minimize the total cost, including selection, purchase, holding and shortage costs. The problem is modeled as a Mixed Integer Programming (MIP). Properties of the problem are explored and a branch-bound algorithm is proposed for it. Also, a simple algorithm for the subproblem is proposed based on its special structure. Numerical experiments are conducted to evaluate the performance of the algorithm and some managerial insights are obtained.

Application of AHP and ANP in supplier selection process-a case in an automotive company

Most organizations prefer to outsource the activities which are not cost-efficient. With regard to the huge amount ofexpenditure in this area, proper selection of the desirable suppliers becomes significant. Previous studies indicated that the criteriaof supplier selection might not be always independent, and this fact implies the existence of interdependencies among them that mayaffect the supplier selection. This study presents and compares two multi-attribute decision making (MADM) techniques to dealwith the supplier selection problem with and without interdependency. An Analytic Hierarchy Process (AHP), and its extension,Analytic Network Process (ANP) are applied to find the final priorities of the suppliers respectively for the cases of independencyand interdependency in an automotive manufacturing company. The two techniques lead to different rankings for the potentialsuppliers. Thus, a Preemptive Goal Programming (PGP) with two goals, maximizing the Total Value of Purchasing and minimizingthe Total Cost of Purchasing, to decide which method is the best was conducted. The whole process is illustrated in a case study.The results from the company of the case study showed that the ANP had the optimal TCP of 1,290 US dollars, while the valuefor AHP was 1,710 USD. However, comparing the TVP value for the two methods shows a negligible difference.

Marketing Of Local Spices In Owerri Municipal Of Imo State, Nigeria

This study examined the marketing of local spices in Owerri municipal of Imo State, Nigeria. The objectives were to examine the costs and margins of the selected spices and analyze the effect of socio-economic variables on the income of the traders. Data for the study were collected from three markets in Owerri municipal (Ekeonunwa, Relief and New market). The spices investigated were Uziza (Piper guineese), Ehuru (Mondora myristica) and Dawadawa (Parkia biglobosa) because they are the most preferred local spices used by the inhabitants of Owerri municipal. Questionnaire was used to collect information from randomly sampled respondents. The type of data collected included socio-economic characteristic of the spices traders, purchase and sales transactions, marketing cost and marketing margins, regression analysis was used to analyze the influence of socio-economic variable on the traders income descriptive statistics such as means, percentages and charts were used to analyze the costs and margins of the selected spices. The result showed that gender, marital status, occupation, trading experience household size, purchase location storage cost, total loading cost, total off-loading cost, total packaging cost and total purchasing cost influenced income of spice traders. The major problems affecting the traders are lack of capital, transportation problem, lack of market information and poor storage facilities. Policy measures were recommended in form of micro- credit facilities and improvement of social infrastructure in the areas of purchase and sale. Keywords: marketing, local spicesJournal of Agriculture and Social Research Vol. 7 (1) 2007: pp. 101-106

Integrated analytical hierarch process and mathematical programming to supplier selection problem with quantity discount

In this article an integration of analytical hierarchy process and non-linear integer and multi-objective programming under some constraints such as quantity discounts, capacity, and budget is applied to determine the best suppliers and to place the optimal order quantities among them. This integration-based multi-criteria decision making methodology takes into account both qualitative and quantitative factors in supplier selection. While the analytical hierarchy process matches item characteristics with supplier characteristics, non-linear integer programming model analytically determines the best suppliers and the optimal order quantities among the determined suppliers. The objectives of the mathematical models constructed are maximizing the total value of purchase (TVP), minimizing the total cost of purchase (TCP) or maximizing TVP and minimizing TCP simultaneously. In addition, several “what if” scenarios are facilitated and the quality of the resulting models is evaluated on real-life data.

A Fairness Perspective on the Use of Total Cost of Ownership in Interfirm Negotiations

We apply a fairness approach to study the use of total cost of ownership (TCO) versus traditional purchasing (TP) information in buyer-supplier contract negotiations under different supply chain problems. We report the results of a 2 by 3 between subjects design in which we manipulate the buyer's type of purchasing information (TCO vs. TP) and the type of supply chain problem (external problem, buyer problem or supplier problem). Under TP information, the buyer's profit is higher with an external problem than with problems caused by either the supplier or the buyer. TCO information allows the buyer to improve its profits when the buyer is the cause of the problem. However, in case of a supplier problem, TCO has no value over TP information: the supplier perceives the buyer's use of TCO information to persuade the supplier to adopt other contract solutions as unfair. In addition, this reaction decreases the interfirm cooperation and joint profit.

Integrated Fuzzy AHP and Weighted-Fuzzy Goal Programming Approach to Solve Supplier Selection Problem with Subjective Factors

Fuzzy goal programming (FGP) method used in supplier selection process shows that decision maker preferences on each fuzzy goal are not yet considered. In order to accommodate those preferences, that are stated as weight on each fuzzy goal, and called weighted fuzzy goal programming (WFGP) method. Then, the developed method is utilized to solve international supplier selection problem. There would be 4 objective functions developed i.e. to minimize net cost, to minimize late delivery, to minimize net rejected material, as well as to maximize business relationship. Maximization of business relationship objective function is intended to obtain right suppliers related to it score. Those objective functions are optimized subject to total demand, maximum supplier capacity, total purchasing cost based on owner estimate, and minimum order requested by suppliers. Linguistic variables are used to measure criterions in business relationship factor. To do so, fuzzy analytic hierarchy process (FAHP) transforms that qualitative manner in linguistic variables to numerical number as a constant in business relationship objective function. Those proposed method provides enhanced solution that represent decision maker preferences than FGP. That is exhibited with equal relationship between weighted goals value and the output of those weighted goals.

On an EPQ model for deteriorating items under permissible delay in payments

This paper derives a production model for the lot-size inventory system with finite production rate, taking into consideration the effect of decay and the condition of permissible delay in payments, in which the restrictive assumption of a permissible delay is relaxed to that at the end of the credit period, the retailer will make a partial payment on total purchasing cost to the supplier and pay off the remaining balance by loan from the bank. At first, this paper shows that there exists a unique optimal cycle time to minimize the total variable cost per unit time. Then, a theorem is developed to determine the optimal ordering policies and bounds for the optimal cycle time are provided to develop an algorithm. Numerical examples reveal that our optimization procedure is very accurate and rapid. Finally, it is shown that the model developed by Huang [1] can be treated as a special case of this paper.

An integrated product returns model with logistics and marketing coordination

We develop an integrated approach for analyzing logistics and marketing decisions within the context of designing an optimal returns system for a retailer servicing two distinct market segments. At the operational level, we show that the optimal refund price is not unique. Moreover, it is such that if both market segments return a purchased product, then neither segment will receive a full money-back refund; and it is such that if one or both segments do not return a purchased product, then a refund premium over the purchase price is possible, but the refund premium will not be enough to offset a customer's total net cost of purchase and return. We also show that any improvement to the returns system that results in increased logistical efficiency or marketing effectiveness will be accompanied by an increase in the selling price of the product. At the strategic level, we show that if the retailer does not coordinate its logistics and marketing efforts to improve the overall returns system, then it will tend to over-invest in one of the functions and under-invest in the other. Finally, we illustrate how our model can be generalized to the case in which a customer's ex post valuation of the product falls along a continuum.

Towards the development of risk-constrained optimal bidding strategies for generation companies in electricity markets

In the competitive electricity market environment, generation dispatching is bid-based, and individual generation companies (Gencos) are required to compete with rivals through bidding to the market. Competition implies the opportunities for Gencos to get more profit and, in the meantime, the risk of not being dispatched. As a result, it has become a major concern for Gencos to build optimal bidding strategies so as to maximize profits while minimizing risks associated. In this paper, a new approach is developed for building optimal bidding strategies with risks taken into account for Gencos participating in a pool-based single-buyer electricity market. It is assumed that each Genco bids a linear supply function and that the system is dispatched to minimize the total purchasing cost of the single-buyer. Each Genco chooses the coefficients in the linear supply function for making tradeoff between two conflicting objectives: profit maximization and risk minimization. A stochastic optimization model is established for the purpose and a novel method for solving this problem is presented. Numerical test results for a simulated electricity market with six Gencos show clearly the essential features of the developed model and method.

A DECISION SUPPORT SYSTEM FOR SUPPLIER SELECTION PROCESS

Today's global business environment, characterized by unprecedented competitive pressures and sophisticated customers that demand speedy solution creates a bigger set of potential suppliers to evaluate and to choose from. To deal with the complexities of the supplier selection process, an integration of Quality Function Deployment (QFD), Analytical Hierarchy Process (AHP) and Preemptive Goal Programming (PGP) techniques is proposed. A QFD matrix is used to display the degree of relationship between each pair of requirement for suppliers and supplier evaluating criterion. This paper employs the AHP first to measure the relative importance weighting for each of the requirements in the QFD process. Secondly, it is used to assess the evaluating score for each of the candidate suppliers for each particular supplier-evaluating criterion. PGP is built to deal with some suppliers' constraints such that the total value of purchase (TVP) becomes maximum and the total cost of purchase (TCP) minimum.

Order allocation in a multiple-supplier environment

The objective of this article is to study the effects of an order allocation procedure in a supply chain. This supply chain consists of a company that can order products from multiple suppliers. At any time of an order, decisions have to be made by the company concerning the allocation of products to the suppliers and the respective order quantities, so that the total purchasing cost is minimized, while maintaining a specified service level. For this purpose, we have developed a solution algorithm and tested it to examine its effectiveness in terms of the service level and the company's total purchasing cost. The final section of the paper summarizes the conclusions of this study and suggests directions for future research.

Total cost of ownership purchasing of a service: The case of airline selection at Alcatel Bell

The multiple objective problem of purchasing for business falls into two broad categories: the purchasing of components for manufacturing and the purchasing of services. Several supplier selection models have been suggested in the literature for the purchasing of production-related components. To our knowledge, no supplier selection model for the purchasing of services has been published. In this paper we elaborate on a mathematical programming model that selects suppliers of a multiple item service and simultaneously determines market shares of the suppliers selected. The methodology is based on the collection of total cost of ownership (TCO) information, quantifying all the costs associated with the purchasing process throughout the entire value chain of the firm. We apply this methodology to the real life case study of selecting airlines for 56 destinations at Alcatel Bell and have obtained TCO savings of 19.5%.

Optimal retailer's replenishment policy for the EPQ model under the supplier's trade credit policy

This paper investigates the optimal replenishment policy under conditions of permissible delay in payments within an economic production quantity (EPQ) framework. In 1985, Goyal assumed that: 1. The unit selling price and the unit purchasing price are equal. 2. The replenishment rate is infinite. 3. At the end of the credit period, the account is settled. The retailer starts paying for higher interest charges on the items in stock and returns money of the remaining balance immediately when the items are sold. The main purpose of this paper is to modify Goyal's model to presume that the unit selling price and the unit purchasing price are not necessarily equal to reflect the real-life situations, and assumes the replenishment rate is finite. Furthermore, this paper will propose that at the end of the credit period, the retailer will make a partial payment on total purchasing cost and pay off the remaining balance by loan from the bank. One theorem is obtained to explore the convexity of the total annual relevant cost function. Three theorems are developed to determine the optimal cycle time and the optimal order quantity. Numerical examples are given to illustrate these theorems.