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    Resource Optimization for Decision Makers
    Indian Institute Of Management Bangalore

    Resource Optimization for Decision Makers

    Indian Institute Of Management Bangalore, Bangalore
    HomeData & AIIndian Institute Of Management BangaloreResource Optimization for Decision Makers
    3 daysDuration
    in-personFormat
    EnglishLanguage
    Data & AITopic

    Next Available Cohort

    Choose your preferred start date

    Oct 5 - Oct 7, 2026
    3 days ยท in-person ยท Instructor-Led ยท Bangalore Campus
    Open
    $1,275

    All-inclusive program fee

    About This Program

    Organizations today - across manufacturing, supply chains, infrastructure, finance, and public administration - are required to make complex decisions under resource constraints. Whether it is allocating budgets, planning production, balancing capacity, optimizing logistics and distribution networks, deploying manpower, or prioritizing projects, decision makers are increasingly expected to justify choices using data-driven, transparent, and defensible frameworks. Optimization techniques - particularly Linear Programming (LP) and Integer Linear Programming (ILP) - enable organizations to identify cost-efficient, capacity-feasible, and operationally sound decisions under multiple constraints and form a core component of modern analytics and operations planning. These methods are among the most widely used, interpretable, and practically relevant tools for decision-making in production planning, supply chain management, logistics, and infrastructure operations, as well as in public-sector planning. Despite their broad applicability, LP and ILP remain underutilized at the managerial and planning level due to their perceived technical complexity. This executive education programme addresses this gap by offering a hands-on, application-oriented introduction to resource optimization using LP and ILP, specifically designed for managers and professionals involved in production, operations, supply chains, planning, and policy. The programme places strong emphasis on problem formulation, interpretation of optimization results, sensitivity and what-if analysis, and managerial decision-making, rather than mathematical abstraction, enabling participants to apply these tools directly to real organizational contexts. Participants will also be exposed to nonlinear optimization, to help them recognize situations where linear models may need extension - such as economies of scale, congestion effects, or nonlinear cost structures - understand trade-offs and model limitations, and engage more effectively with analytics, operations research, and technical teams.

    Why Indian Institute Of Management Bangalore?

    IIM Bangalore occupies a position in Indian management education that no other institution quite replicates โ€” a school shaped by a post-Independence nation-building mandate that has since grown into one of Asia's most respected research and leadership institutions. Its executive education programs draw participants from across India's most consequential industries, from Bengaluru's technology corridor to Mumbai's financial sector, and bring them into contact with faculty who are as likely to be publishing in top-tier academic journals as advising a government ministry.

    Your Profile

    • Professionals with 5-20 years of experience involved in resource planning, allocation, operations, logistics, or supply chain management.
    • Managers and officers in budgeting, project evaluation, analytics, decision support, or policy planning roles.
    • Operations and production managers in manufacturing, infrastructure, energy, utilities, or transportation sectors.
    • PSU and government officers working in planning, finance, or operations who need evidence-based decision frameworks.
    • Consultants and analytics professionals in operations, public policy, or advisory organizations.

    Benefits

    • Formulate real-world operational and planning problems as LP and ILP optimization models.
    • Interpret optimal solutions, sensitivity results, and trade-offs to support managerial decisions.
    • Apply optimization to production planning, supply chain, logistics, scheduling, and budget allocation.
    • Recognize when nonlinear models are needed and understand their practical implications for decision-making.
    • Build transparent and auditable decision-making processes that reduce over-reliance on black-box models.

    What You'll Learn

    • Core Optimization Foundations: role of optimization in managerial and policy decisions; Linear Programming (problem formulation, graphical intuition, managerial interpretation); Integer and Mixed-Integer Programming (discrete decisions, yes/no selection, assignment problems, practical relevance in planning and allocation).
    • Applied Resource Optimization: production, capacity, and workforce planning; budget allocation and project prioritization; transportation, logistics, and supply chain optimization; scheduling and assignment problems.
    • Model Interpretation and Robustness: sensitivity analysis and shadow prices; trade-offs and what-if analysis; understanding model assumptions and limitations.
    • Introduction to Nonlinear Optimization: when and why nonlinear models arise; examples of nonlinear objectives and constraints; convex vs non-convex problems (managerial intuition); practical implications for decision makers.
    • Tools and Hands-on Exposure: Excel Solver implementation of LP, ILP, NLP; interpreting solver outputs for managerial decisions.
    • Case Studies and Applied Exercises: corporate and PSU-oriented cases; participant-driven problem formulation exercises.

    Frequently Asked Questions

    How to Apply

    1. 1

      Check your eligibility

      Review the entry requirements listed on this page. Most executive programs require 8โ€“15 years of professional experience.

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    3. 3

      Contact the school

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    4. 4

      Prepare your application

      Gather your CV, reference letters, and any required test scores. Many EMBA programs waive standardised tests for senior candidates.

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