M. M. E. Alemany

Mathematical programming model for centralised master planning in ceramic tile supply chains

The object of this article is to develop a centralised replenishment, production, and distribution model for ceramic tile supply chains. These supply chains are assumed to be multi-item, multi-supplier, multi-facility, multi-type and multi-level distribution centres. The model deals with multi-period master planning where sourcing considerations for replenishments, production facilities, and distribution centres are important to maximise an objective function involving the total net profit. This model is deterministic and has been formulated as a mixed-integer linear programming (MILP) model. An example based on modifications of real-world industrial problems is presented.

A review of mathematical models for supporting the order promising process under Lack of Homogeneity in Product and other sources of uncertainty

The OPP combined with LHP is little researched.The OPP with uncertainty conditions in variables is little researched.The OPP combined with LHP and uncertainty becomes a research stream. This paper presents a review of mathematical programming models for supporting the order promising process (OPP) under Lack of Homogeneity in Product (LHP) conditions and uncertainty in a modelling approach. LHP appears in productive processes with raw materials, which directly stem from nature and/or production processes with operations that confer heterogeneity to the characteristics of the outputs obtained, even when the inputs used are homogenous. LHP has a direct impact on the companys service level, mainly when the customer needs to be served with homogeneous units of the same product. LHP leads to inherent sources of uncertainty due to the natural physical characteristics of the supply chain. This research aims to determine the way that LHP, and uncertainties related either to LHP or different variables that confer more realistic conditions to OPP, have been modelled in different LHP sectors, or others affected by uncertainty. This result may provide the opportunity to transfer knowledge among them and to identify gaps for further research. Accordingly, and in order to set the basis for future research into the OPP topic, for cases affected by LHP and for uncertainties inherent to LHP conditions, or due to other possible uncertain variables, this research needs to consider both mathematical model types: (i) mathematical programming models of the OPP that consider some LHP characteristic and (ii) mathematical programming models of the OPP that consider any type of uncertainty in the modelling approach. We propose a taxonomy approach to classify and analyse the literature based on the main characteristics of its environment, order promising approach, customer order characteristics, modelling characteristics, and LHP and uncertainty modelling. The main finding of this research was that research into OPP modelling, combined with LHP characteristics and uncertainty, are lacking. We provide some starting points for further research in this field.

Application of particle swarm optimisation with backward calculation to solve a fuzzy multi-objective supply chain master planning model

Traditionally, supply chain planning problems consider variables with uncertainty associated with uncontrolled factors. These factors have been normally modelled by complex methodologies where the seeking solution process often presents high scale of difficulty. This work presents the fuzzy set theory as a tool to model uncertainty in supply chain planning problems and proposes the particle swarm optimisation PSO metaheuristics technique combined with a backward calculation as a solution method. The aim of this combination is to present a simple effective method to model uncertainty, while good quality solutions are obtained with metaheuristics due to its capacity to find them with satisfactory computational performance in complex problems, in a relatively short time period.

A MODEL-DRIVEN DECISION SUPPORT SYSTEM FOR REALLOCATION OF SUPPLY TO ORDERS UNDER UNCERTAINTY IN CERAMIC COMPANIES

AbstractIn ceramic companies, uncertainty in the tone and gage obtained in first quality units of the same finished good (FG) entails frequent discrepancies between planned homogeneous quant- ities and real ones. This fact can lead to a shortage situation in which certain previously committed customer orders cannot be served because there are not enough homogeneous units of a specific FG (i.e., with the same tone and gage). In this paper, a Model-Driven Decision Support System (DSS) is proposed to reassign the actual homogeneous stock and the planned homogeneous sublots to already committed orders under uncertainty by means of a mathematical programming model (SP-Model). The DSS functionalities enable ceramic decision makers to generate different solutions by changing model options. Uncertainty in the planned homogeneous quantities, and any other type of uncertainty, is managed via scenarios. The robustness of each solution is tested in planned and real situations with another DSS functionality based on a...

Conceptual Framework for Managing Uncertainty in a Collaborative Agri-Food Supply Chain Context.

Agri-food supply chains are subjected to many sources of uncertainty. If these uncertainties are not managed properly, they can have a negative impact on the agri-food supply chain (AFSC) performance, its customers, and the environment. In this sense, collaboration is proposed as a possible solution to reduce it. For that, a conceptual framework (CF) for managing uncertainty in a collaborative context is proposed. In this context, this paper seeks to answer the following research questions: What are the existing uncertainty sources in the AFSCs? Can collaboration be used to reduce the uncertainty of AFSCs? Which elements can integrate a CF for managing uncertainty in a collaborative AFSC? The CF proposal is applied to the weather source of uncertainty in order to show its applicability.

Fuzzy sets to model master production effectively in Make to Stock companies with Lack of Homogeneity in the Product

Supply chains (SCs) with Lack of Homogeneity in the Product (LHP) present inherent sources of uncertainty due to the heterogeneity of raw materials and uncontrollable productive factors. LHP SCs are characterized by producing units of the same finished goods that are not homogeneous. However, the exact quantity of each one in a production lot will only be known when it is produced. These SCs must classify finished goods into subtypes according to customer requirements. In this paper, a fuzzy mathematical programming model is proposed. To match homogeneity customer requirements with the sizing of production lots, the proposed master plan considers two main aspects: 1) forecast demand is expressed in terms of number of orders with a similar order size; 2) LHP is modeled by considering that each production lot is split into several homogeneous sub-lots. Then uncertainty is considered by means of fuzzy sets in order sizes and homogeneous sub-lots quantities. The fuzzy model is evaluated by emulating real conditions and is compared with the equivalent deterministic one to assess its robustness. The results demonstrate that the fuzzy approach outperforms the deterministic one and that it is more effective for handling real situations when LHP is present.

Measuring Competencies in Higher Education. The Case of Innovation Competence

Within the context of permanent change, innovation has become a vital value for the survival and development of the organisations. The development of this increasingly important value will help students to gain access to the labour market and to adapt to their future jobs in accordance with these characteristics. Competency describes what training participants should be able to do at the end of such training. Competency is acquired through the various learning objectives to be achieved. Innovation competency is closely related to Self-assessment and the learning methods, Ability to work in interactive communication situations, Ability to create and maintain connections work, Ability to cooperate in a multidisciplinary and multicultural environment and Ability to communicate and interact in an international environment, etc. In this chapter, we develop a method for measuring the innovation competencies in higher education by introducing different levels of mastery.

A Fuzzy Order Promising Model With Non-Uniform Finished Goods

Traditionally, the homogeneity of available units of the same finished good (FG

Identifying the Main Uncertainties in the Agri-Food Supply Chain

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