Order allocation in a multi-supplier environment: review of the literature since 2007

Purpose: Optimal order allocation on the part of the buyer in a multi-supplier environment has become a major concern in supply chains. There are numerous articles that analyze and present models for optimizing order allocation from a given panel of suppliers. The purpose of this paper is to provide an analysis on this topic which considers: (i) aims, (ii) results, (iii) model complexity, and (iv) resolution procedures. Design/methodology/approach: The paper reviews twenty-eight articles, twenty-one of them published since 2007 in journals indexed by Journal Citation Reports (in ISI Web of Knowledge) on this topic. Findings and Originality/value: This review reveals four main aspects mentioned as determinant in generating mathematical models. The analysis of these four points does not allow for a single, overarching model. Rather, all analyzed solutions reflect and respond to a specific company environment. Originality/value: A global analysis on several recent papers, describing main aspects wich determines optimal order allocation in multi-supplier environment.Peer Reviewe

Order allocation in a multi-supplier environment: review of the literature since 2007

Purpose: Optimal order allocation on the part of the buyer in a multi-supplier environment has become a major concern in supply chains. There are numerous articles that analyze and present models for optimizing order allocation from a given panel of suppliers. The purpose of this paper is to provide an analysis on this topic which considers: (i) aims, (ii) results, (iii) model complexity, and (iv) resolution procedures. Design/methodology/approach: The paper reviews twenty-eight articles, twenty-one of them published since 2007 in journals indexed by Journal Citation Reports (in ISI Web of Knowledge) on this topic. Findings: This review reveals four main aspects mentioned as determinant in generating mathematical models. The analysis of these four points does not allow for a single, overarching model. Rather, all analyzed solutions reflect and respond to a specific company environment. Originality/value: A global analysis on several recent papers, describing main aspects wich determines optimal order allocation in multi-supplier environment.Postprint (published version

Wood-based construction project supplier selection under uncertain starting date

There is a growing interest in supply management systems in today's competitive business environment. Importance of implementing supply management systems especially in home construction industry is due to the fact that several risks arising from different sources can adversely affect the project financially or its timely completion. Some risks of construction projects are out of managers' control while other risks such as supply related ones can usually be controlled and directed by effective managerial tactics. In this paper, we address the supplier selection problem (SSP) in wood-based construction industry (housing projects) in the presence of project commencement uncertainties. Based on the suppliers' (vendors') reaction towards these uncertainties in the delivery time, we explore two cases: (a) supplier selection with buyer penalty for a delay (SSPD) where the price of product increases with the delay; (b) supplier selection with quantity reduction for a buyer delay (SSQRD). Three heuristic-based supplier selection approaches are proposed and tested on randomly generated data sets. The proposed approaches show promising result

Asignación óptima de pedidos: revisión del estado del arte desde el año 2007

La asignación óptima de pedidos, por parte de un comprador, en un entorno multiproveedor ha adquirido gran importancia en el ámbito actual de la cadena de aprovisionamiento. Hay diversos artículos que analizan y exponen modelos que permiten la optimización de dicha asignación respecto a un panel de proveedores dado. El artículo actual revisa un total de diez artículos que tratan esta temática y que han sido publicados desde el año 2007 hasta la actualidad, en revistas indexadas por Journal Citation Reports (en ISI Web ok Knowledge), además de otras publicaciones en trabajos académicos y en congresos. De esta forma se realiza un análisis que permite responder a; (i) tipo de procedimiento de resolución utilizado, (ii) objetivos planteados, (iii) resultados obtenidos y (iv) complejidad de los modelos. El análisis conjunto de estos cuatro puntos no permite determinar la existencia de un modelo global, por el contrario, todas las soluciones analizadas reflejan y dan respuesta a entornos determinados.Preprin

Meta-heuristic Algorithms for an Integrated Production-Distribution Planning Problem in a Multi-Objective Supply Chain

In today's globalization, an effective integration of production and distribution plans into a unified framework is crucial for attaining competitive advantage. This paper addresses an integrated multi-product and multi-time period production/distribution planning problem for a two-echelon supply chain subject to the real-world variables and constraints. It is assumed that all transportations are outsourced to third-party logistics providers and all-unit quantity discounts in transportation costs are taken into consideration. The problem has been formulated as a multi-objective mixed-integer linear programming model which attempts to simultaneously minimize total delivery time and total transportation costs. Due to the complexity of the considered problem, genetic algorithm (GA) and particle swarm optimization (PSO) algorithm are developed within the LP-metric method and desirability function framework for solving the real-sized problems in reasonable computational time. As the performance of meta-heuristic algorithms is significantly influenced by calibrating their parameters, Taguchi methodology has been used to tune the parameters of the developed algorithms. Finally, the efficiency and applicability of the proposed model and solution methodologies are demonstrated through several problems in different size

Order allocation in a multiple-vendor and quantity discount environment: A multi-objective decision making approach

Integrated supplier selection and order allocation is a complex problem that is important for both designing and operating supply chains. It becomes especially complicated when quantity discounts are considered at the same time. Under such circumstances, most studies often formulate the problem as a Multi-Objective Linear Programming problem (MOLP), and then transform it to a Mixed Integer Programming problem (MIP) to handle the inherited multi-objectives, simultaneously. But, objectives are not of equal importance and in this approach scaling and subjective weighting often are not considered. In addition, some of the studies that use weighting method to solve the MOLP, usually ignore to normalize the coefficients. However, as different coefficients have different units such as cost or number coefficients, so weighted summation will be meaningless. Furthermore, in most of the studies only quantitative criteria are considered in mathematical model. But, the importance of some qualitative criteria persuade decision maker to consider other affective criteria as well as cost. In this study, in order to ease the problem and to obtain a more reasonable compromised solution for order allocating among suppliers, an integration of analytical hierarchy process and linear integer and multi-objective programming is proposed. The large number of criteria and attributes are employed in this problem and they are employed in a comprehensive model to solve the multi-objective problem and to find the most preferred non dominated solutions by considering decision maker’s (DM) preferences. Some illustrative examples are solved using LINGO and the results are compared. The sensitivity analysis and comparing the results with one of the well-known studies in the literature has demonstrated the flexibility and efficiency of the proposed model to deal with large sized problems and incorporate different purchasing policies, easily and in a short amount of time

Heuristics for Sourcing from Multiple Suppliers with Alternative Quantity Discounts

In this paper, we analyze the impact of supplier pricing schemes and supplier capacity limitations on the optimal sourcing policy for a single firm. We consider the situation where the total quantity to be procured for a single period is known by the firm and communicated to the supplier set. In response to this communication, each supplier quotes a price and a capacity limit in terms of a maximum quantity that can be supplied to the buyer. Based on this information, the buyer makes a quantity allocation decision among the suppliers and corresponding to this decision is the choice of a subset of suppliers who will receive an order. Based on industry observations, a variety of supplier pricing schemes from the constituent group of suppliers are analyzed, including linear discounts, incremental units discounts, and all units discounts. Given the complexity of the optimization problem for certain types of pricing schemes, heuristic solution methodologies are developed to identify a quantity allocation decision for the firm. Through an extensive computational comparison, we find that these heuristics generate near-optimal solutions very quickly. Data from a major office products retailer is used to illustrate the resulting sourcing strategies given different pricing schemes and capacity limitations of suppliers in this industry. We find for the case of capacity constrained suppliers, the optimal quantity allocations for two complex pricing schemes (linear discount, and incremental units discount) are such that at most one selected supplier will receive an order quantity that is less than its capacity