Format: Live instructor-led online training via Zoom / Microsoft Teams

Operations Research Techniques Training Course

Course Introduction

The Operations Research Techniques Training Course is designed to equip participants with practical knowledge and analytical skills in applying quantitative methods and mathematical models to solve complex organizational problems and improve decision-making processes. In today's highly competitive and data-driven environment, organizations increasingly rely on operations research techniques to optimize resource utilization, enhance operational efficiency, improve productivity, and achieve strategic objectives. This course provides participants with comprehensive competencies in operations research methodologies, optimization techniques, forecasting models, simulation methods, and decision analysis tools that support evidence-based management and organizational performance improvement.

The course focuses on the fundamental and advanced concepts of operations research, including linear programming, transportation and assignment models, inventory management, network analysis, queuing theory, decision analysis, simulation modeling, forecasting techniques, and project management methodologies. Participants will gain practical experience in developing and applying mathematical models and analytical techniques to address challenges in production planning, logistics management, resource allocation, supply chain optimization, and service delivery systems.

As organizations increasingly seek efficient and innovative solutions to operational and strategic challenges, operations research has become an essential discipline in business management, manufacturing, healthcare, government, transportation, finance, and development sectors. This training emphasizes analytical thinking, problem-solving capabilities, optimization strategies, and data-driven decision-making approaches that enable organizations to improve efficiency, reduce costs, manage risks, and enhance competitiveness in dynamic operating environments.

Through presentations, practical exercises, group assignments, computer-based applications, and real-world case studies, participants will develop competencies necessary to formulate, analyze, and solve operational problems using operations research techniques. Upon completion of this course, participants will be capable of applying quantitative analytical tools to optimize organizational processes, improve resource management, support strategic planning, and strengthen evidence-based operational decision-making.

Course Objectives

Upon completion of this course, participants will be able to:

1.     Understand the principles and applications of operations research techniques.

2.     Formulate organizational problems using quantitative models and analytical frameworks.

3.     Apply optimization techniques for resource allocation and operational planning.

4.     Utilize linear programming and network models for decision-making.

5.     Apply inventory management and forecasting methods effectively.

6.     Conduct simulation and decision analysis for complex operational challenges.

7.     Analyze queuing systems and service delivery processes.

8.     Develop and interpret operations research models and solutions.

9.     Prepare analytical reports and recommendations for management decision-making.

10.  Utilize operations research techniques to improve organizational efficiency and productivity.

Organizational Benefits

Organizations that invest in this training will benefit by:

1.     Enhancing evidence-based operational decision-making capabilities.

2.     Improving resource allocation and utilization efficiency.

3.     Reducing operational costs and process inefficiencies.

4.     Strengthening strategic planning and forecasting processes.

5.     Improving inventory management and supply chain performance.

6.     Enhancing project planning and operational scheduling systems.

7.     Strengthening risk management and scenario planning capabilities.

8.     Building staff competencies in analytical problem-solving techniques.

9.     Improving productivity and service delivery effectiveness.

10.  Strengthening organizational competitiveness, profitability, and sustainability.

Target Participants

This course is designed for operations managers, project managers, production managers, supply chain specialists, logistics officers, business analysts, planners, engineers, financial analysts, monitoring and evaluation specialists, government officials, consultants, researchers, data analysts, and professionals responsible for operational planning, resource management, process optimization, and evidence-based decision-making.

Course Outline

Module 1: Foundations of Operations Research

1.     Principles and concepts of operations research

2.     Historical development and applications of operations research

3.     Operations research process and problem formulation

4.     Systems thinking and analytical decision-making

5.     Mathematical modeling principles and approaches

6.     General Case Study: Identifying operational inefficiencies and developing analytical models for process improvement

Module 2: Linear Programming Techniques

1.     Principles of linear programming models

2.     Formulation of objective functions and constraints

3.     Graphical methods of solving linear programming problems

4.     Simplex method and optimization procedures

5.     Sensitivity and post-optimality analysis

6.     General Case Study: Optimizing production schedules and resource allocation in manufacturing operations

Module 3: Transportation and Assignment Models

1.     Principles of transportation modeling

2.     Transportation problem formulation and optimization

3.     Assignment model concepts and applications

4.     Hungarian method and allocation techniques

5.     Applications in logistics and distribution systems

6.     General Case Study: Optimizing transportation routes and distribution networks

Module 4: Inventory Management and Forecasting Techniques

1.     Principles of inventory management systems

2.     Economic order quantity and reorder point models

3.     Inventory control and stock management techniques

4.     Demand forecasting methods and applications

5.     Time series forecasting and trend analysis

6.     General Case Study: Developing inventory management systems for retail supply chains

Module 5: Network Analysis and Project Management

1.     Principles of network analysis techniques

2.     Program Evaluation and Review Technique (PERT)

3.     Critical Path Method (CPM) applications

4.     Project scheduling and resource planning

5.     Time-cost trade-off analysis and optimization

6.     General Case Study: Planning and scheduling a large infrastructure development project

Module 6: Queuing Theory and Service System Analysis

1.     Principles of queuing systems and waiting line models

2.     Components and characteristics of queuing models

3.     Performance measures and service efficiency analysis

4.     Single-channel and multi-channel queuing systems

5.     Applications in service operations and capacity planning

6.     General Case Study: Improving customer service efficiency in banking operations

Module 7: Decision Analysis and Decision Trees

1.     Principles of decision analysis

2.     Decision-making under certainty and uncertainty

3.     Decision trees and expected value analysis

4.     Risk assessment and sensitivity analysis techniques

5.     Multi-criteria decision-making approaches

6.     General Case Study: Evaluating investment alternatives under uncertain market conditions

Module 8: Simulation Modeling Techniques

1.     Principles and concepts of simulation modeling

2.     Types of simulation methods and applications

3.     Monte Carlo simulation techniques

4.     Model development and validation procedures

5.     Interpretation and utilization of simulation results

6.     General Case Study: Simulating production processes and operational scenarios

Module 9: Dynamic Programming and Optimization Methods

1.     Principles of dynamic programming

2.     Multi-stage decision-making models

3.     Recursive optimization techniques

4.     Applications in resource planning and allocation

5.     Optimization under constraints and uncertainties

6.     General Case Study: Optimizing investment and resource allocation decisions

Module 10: Supply Chain and Logistics Optimization

1.     Principles of supply chain management and optimization

2.     Distribution network design techniques

3.     Facility location and capacity planning models

4.     Procurement and logistics management optimization

5.     Performance measurement and continuous improvement

6.     General Case Study: Optimizing supply chain operations for improved service delivery

Module 11: Computer Applications in Operations Research

1.     Introduction to operations research software tools

2.     Spreadsheet modeling and optimization applications

3.     Computer-based simulation and forecasting tools

4.     Data management and analytical reporting techniques

5.     Visualization and presentation of analytical findings

6.     General Case Study: Using analytical software to solve complex operational problems

Module 12: Emerging Trends and Applications of Operations Research

1.     Big data analytics and operations research integration

2.     Artificial intelligence and predictive optimization techniques

3.     Digital transformation and advanced decision support systems

4.     Operations research applications in sustainable development

5.     Future trends and innovations in operations research

6.     General Case Study: Designing data-driven operational strategies for organizational transformation

General Information

1.     Customized Training: All our courses can be tailored to meet the specific needs of participants.

2.     Language Proficiency: Participants should have a good command of the English language.

3.     Comprehensive Learning: Our training includes well-structured presentations, practical exercises, web-based tutorials, and collaborative group work. Our facilitators are seasoned experts with over a decade of experience.

4.     Certification: Upon successful completion of training, participants will receive a certificate from Foscore Development Center (FDC-K).

5.     Training Locations: Training sessions are conducted at Foscore Development Center (FDC-K) centers. We also offer options for in-house and online training, customized to the client's schedule.

6.     Flexible Duration: Course durations are adaptable, and content can be adjusted to fit the required number of days.

7.     Onsite Training Inclusions: The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a Certificate of Successful Completion. Participants are responsible for their travel expenses, airport transfers, visa applications, dinners, health/accident insurance, and personal expenses.

8.     Additional Services: Accommodation, pickup services, freight booking, and visa processing arrangements are available upon request at discounted rates.

9.     Equipment: Tablets and laptops can be provided to participants at an additional cost.

10.  Post-Training Support: We offer one year of free consultation and coaching after the course.

11.  Group Discounts: Register as a group of more than two and enjoy a discount ranging from 10% to 50%.

12.  Payment Terms: Payment should be made before the commencement of the training or as mutually agreed upon, to the Foscore Development Center account. This ensures better preparation for your training.

13.  Contact Us: For any inquiries, please reach out to us at training@fdc-k.org or call us at +254712260031.

14.  Website: Visit our website at www.fdc-k.org for more information.