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This book presents examples of engineering applications; particularly Industrial Engineering applications. Six distinct cases are included. The applications range from product design to quality control. The emphasis is on developing methodologies that can enhance utilization of resources. Case studies are important in demonstrating the use of engineering design principles and methodologies. The published literature, however, shows a paucity of cases that may be used for teaching and learning purposes. The reasons for a dearth of published case studies are many, including the propriety nature of problems and confidentiality of data. Such issues are further aggravated as many companies are self-insured and are reluctant to share information with outsiders.

Resource allocation --- Industrial engineering --- Management engineering --- Simplification in industry --- Engineering --- Value analysis (Cost control) --- Allocation of resources --- Resources allocation --- Economics --- Management --- Operations research --- Organization --- Planning --- Feasibility studies

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Since the late 1940s, linear programming models have been used for many different purposes. Airline companies apply these models to optimize their use of planes and staff. NASA has been using them for many years to optimize their use of limited resources. Oil companies use them to optimize their refinery operations. Small and medium-sized businesses use linear programming to solve a huge variety of problems, often involving resource allocation. In my study, a typical product-mix problem in a manufacturing system producing two products (each product consists of two sub-assemblies) is solved for its optimal solution through the use of the latest versions of MATLAB having the command simlp, which is very much like linprog. As analysts, we try to find a good enough solution for the decision maker to make a final decision. Our attempt is to give the mathematical description of the product-mix optimization problem and bring the problem into a form ready to call MATLAB's simlp command. The objective of this study is to find the best product mix that maximizes profit. The graph obtained using MATLAB commands, give the shaded area enclosed by the constraints called the feasible region, which is the set of points satisfying all the constraints. To find the optimal solution we look at the lines of equal profit to find the corner of the feasible region which yield the highest profit. This corner can be found out at the farthest line of equal profit, which still touches the feasible region. The most critical part is the sensitivity analysis, using Excel Solver, and Parametric Analysis, using computer software, which allows us to study the effect on optimal solution due to discrete and continuous change in parameters of the LP model including to identify bottlenecks. We have examined other options like product outsourcing, one-time cost, cross training of one operator, manufacturing of hypothetical third product on under-utilized machines and optimal sequencing of jobs on machines.

Resource allocation --- Linear programming --- Production scheduling --- Programming (Mathematics) --- Allocation of resources --- Resources allocation --- Economics --- Management --- Operations research --- Organization --- Planning --- Feasibility studies --- MATLAB. --- Microsoft Excel Solver (Computer program) --- MATLAB (Computer program) --- Matrix laboratory --- E-books --- MATLAB (Computer file)

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Consumers --- Econometric models --- Resource allocation --- 330.115 --- Econometrics --- Mathematical models --- 330.115 Econometrie --- Econometrie --- Allocation of resources --- Resources allocation --- Economics --- Management --- Operations research --- Organization --- Planning --- Feasibility studies --- Customers (Consumers) --- Shoppers --- Persons --- Quantitative methods (economics)

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Households --- Economic development --- Resource allocation --- Business & Economics --- Economic Theory --- Allocation of resources --- Resources allocation --- Economics --- Management --- Operations research --- Organization --- Planning --- Feasibility studies --- Population --- Families --- Home economics --- Economic aspects --- Congresses --- Research

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Fragile states lag far behind meeting the Millennium Development Goals (MDGs) by 2015, representing 75% of the MDG deficit. Fragile states already lacked the institutional strength to adequately respond to both financial and environmental shocks. The effects of three consecutive and inter-related shocks – food, fuel and the secondary effects of the financial crisis – risk reversing progress achieved by some post-conflict states, and further entrenching insecurity in others. Although official development assistance to fragile states is growing in real terms, it is increasingly concentrated, and half of fragile states face the prospects of declining aid. There is a need to maintain aid levels and meet aid pledges, but also to improve the quality of support to fragile states. This report serves as a tool to better monitor the levels, timing and composition of resource flows to fragile states, and presents salient facts on aid flows to fragile states, the impact on fragile states of the three crises and the need for a whole-of-government response.

Development aid. Development cooperation --- Polemology --- Resource allocation --- Conflict management --- Conflict control --- Conflict resolution --- Dispute settlement --- Management of conflict --- Managing conflict --- Management --- Negotiation --- Problem solving --- Social conflict --- Crisis management --- Allocation of resources --- Resources allocation --- Economics --- Operations research --- Organization --- Planning --- Feasibility studies