Mathematical Programming Model for Procurement Selection in Water Irrigation Systems. A Case Study

[EN] The development tools to optimize the process and helping management to get margin are used inside of the industrial manufacture. Water networks management are not alien to this need. The optimization of the water resource is currently done in big basins, but it is not a general practice in irrigation networks that operate as water distribution companies to supply the farmers¿ demand. Nowadays, this management is not optimized and the costs are not minimized. This research introduces a mathematical programming model to optimize the replenishment process in a local irrigation network with the aim to decide what volume is procured (source, quantity and timetable) as well as what volume is stored while minimising the involved total costs. The final objective is to improve the sustainability of the water systems. The use of this tool reduces the water costs in 52.2% as well as enables to define the necessary source and the electrical schedule along the year. This definition optimizes the operating of the water system and enables to reduce the water price from 0.23 €/m3 (current water management) to 0.11 €/m3 (proposed model).Pérez-Sánchez, M.; Díaz-Madroñero Boluda, FM.; López Jiménez, PA.; Mula, J. (2017). Mathematical Programming Model for Procurement Selection in Water Irrigation Systems. A Case Study. Journal of Engineering Science and Technology Review (Online). 10(6):146-153. doi:10.25103/jestr.106.17S14615310

A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain

We consider a real-world automobile supply chain in which a first-tier supplier serves an assembler and determines its procurement transport planning for a second-tier supplier by using the automobile assembler's demand information, the available capacity of trucks and inventory levels. The proposed fuzzy multi-objective integer linear programming model (FMOILP) improves the transport planning process for material procurement at the first-tier supplier level, which is subject to product groups composed of items that must be ordered together, order lot sizes, fuzzy aspiration levels for inventory and used trucks and uncertain truck maximum available capacities and minimum percentages of demand in stock. Regarding the defuzzification process, we apply two existing methods based on the weighted average method to convert the FMOILP into a crisp MOILP to then apply two different aggregation functions, which we compare, to transform this crisp MOILP into a single objective MILP model. A sensitivity analysis is included to show the impact of the objectives weight vector on the final solutions. The model, based on the full truck load material pick method, provides the quantity of products and number of containers to be loaded per truck and period. An industrial automobile supply chain case study demonstrates the feasibility of applying the proposed model and the solution methodology to a realistic procurement transport planning problem. The results provide lower stock levels and higher occupation of the trucks used to fulfill both demand and minimum inventory requirements than those obtained by the manual spreadsheet-based method. (C) 2014 Elsevier Inc. All rights reserved.This work has been funded partly by the Spanish Ministry of Science and Technology project: Production technology based on the feedback from production, transport and unload planning and the redesign of warehouses decisions in the supply chain (Ref. DPI2010-19977) and by the Universitat Politecnica de Valencia project 'Material Requirement Planning Fourth Generation (MRPIV) (Ref. PAID-05-12)'.Díaz-Madroñero Boluda, FM.; Peidro Payá, D.; Mula, J. (2014). A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain. Applied Mathematical Modelling. 38(23):5705-5725. https://doi.org/10.1016/j.apm.2014.04.053S57055725382

IZBOR DOBAVLJAČA I VIŠEKRITERIJALNA ANALIZA : Diplomski rad

U ovom je radu prikazan kvantitativni model izbora dobavljača. Model koristi tri metode operacijske pretrage: hijerarhijski proces analize, PROMETHEE metodu i linearno programiranje. Prva metoda, AHP, koristi se za izračun težina svakog kriterija pomoću usporedbe u parovima. Koristeći PROMETHEE metodu alternative (dobavljači) rangiraju se te se izračunavaju koeficijenti preferencije za svakog dobavljača. LP model, koji se temelji na prethodno prikupljenim koeficijentima, distribuira količine narudžbi svakom dobavljaču u svrhu maksimiziranja TVP-a.This thesis presents a supplier selection quantitative model. The model deals with three methods of operation research: Analytic Hierarchy Process, PROMETHEE method and linear programming. The first of them – AHP – is used to calculate the weights of each criteria by pairwise comprehension. By using the PROMETHEE method the alternatives (suppliers) are ranked and preference coefitions for each supplier are calculated. The LP model, which is based on the previous gathered coefitions, distributes order quantities to each supplier in order to maximise the Total Value of Purchasing (TVP)

Supply chain operation strategies and risk management with working capital consideration: a case study of the supply chain of lightning protection products in China

JEL: G32; D21With the advent of economic globalization, competition is increasingly hinged on supply chain. Meanwhile, working capital becomes a key element of a successful supply chain. This thesis researches the supply chain of a typical lightning protection products manufacturer in China, i.e. Company Z. The thesis starts with the working capital issues in the supply chain of Company Z; then, with the help of questionnaires and a sensible indicator system and weight assignments; analyzes and summarizes the status quo of the working capital and related key issues in the supply chain consisting of Company Z and its suppliers and customers. Building on such analysis, a two-dimensional classification matrix is created to divide suppliers and customers into four groups (namely, strategic-type, partner-type, general-type, and bottleneck-type) and supply chain operation strategies are devised for each group. Furthermore, based on such supply chain operations strategies of Company Z, a working capital risk management mechanism with an early warning system is developed, and a supply chain-based financing platform is designed to help the supply chain participants seek financing and share the risks with working capital.Com o advento da era da globalização económica, a cadeia de suprimentos tornou-se cada vez mais importante para a concorrência empresarial, e ao mesmo tempo, o fundo de maneio tornou-se num elemento chave para o sucesso da gestão da cadeia de suprimentos. Neste trabalho, a cadeia de suprimentos de uma empresa chinesa de fabricação de produtos típicos de proteção contra relâmpagos, a empresa Z, é o objeto de estudo. Tomando como ponto de partida os problemas de fundo de maneio existentes na cadeia de suprimentos da empresa Z, por meio de questionários combinados com o estabelecimento de um sistema de indexação e de ponderação, foram realizadas análises precisas sobre problemas-chaves existentes e da situação atual da gestão do fundo de maneio da cadeia de suprimentos a montante e a jusante da empresa Z. Estabeleceram-se matrizes bidimensionais de classificação para respectivamente subdividir os fornecedores e clientes em quatro categorias, a saber, categoria de fornecedores/clientes estratégicos, categoria de fornecedores/clientes parceiros, categoria de fornecedores/clientes comuns e categoria de fornecedores/clientes críticos (“engarrafamentos”) e propor estratégias diferentes na cadeia de suprimentos para diferentes categorias. Por fim, o nosso estudo indica que segundo a estratégia de operação da cadeia de suprimentos da empresa Z, deve ser estabelecido um mecanismo de controle e gestão de risco de fundo de maneio, um sistema de alerta de risco e, ainda, projetar uma plataforma de financiamento a fim de prover o financiamento emergente da cadeia de suprimentos da empresa Z e a partilha dos riscos de gestão do fundo de maneio

Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises