Supply Chain Management Optimization with Meta heuristic

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Supply chain is happening all around you.  If your company somehow makes a product, or procures a product, or procures then makes a product that you then sell to a customer, you have an end-to-end supply chain that might need optimizing. How do you know if your end-to-end supply chain needs optimizing? The litmus test that can use is this: Are you getting your customers what they want, when they want it – and spending as little money as possible accomplishing that?

Optimization is necessary in supply chain management. All stages of a supply chain can be regarded as an optimization problem. Minimizing the total cost of transportation while satisfying customer needs, minimizing inventory holding costs throughout the supply chain while fulfilling the demands of plants or end customers, deciding on the best facility location minimizing the distribution costs are some examples. Supply chain is so inherent in our life that we are at the center of producing or demanding something personally. Main supply chain decisions are about facility location, production, inventory, and transportation. Supply chain decisions may be strategic, tactical, and operational. Decisions are triggered by both customer requirements and efficient supply chain operations. These decisions may conflict with each other. For example, customer satisfaction and mass production to decrease the manufacturing costs result in high inventory levels. So, a production decision has a conflict with an inventory decision. Conflicting decisions require coordination and integration through supply chain to optimize the processes in it globally. Furthermore, Supply chain development is now driven by customers, with shorter lead times and increasing customer expectations. Supply chain optimization is crucial for a successful customer experience.

The overall improvement of the supply chain management that can be accomplished through the use of optimization approaches can be significant. The availability of these approaches opens the door to handling decision-making problems in purchasing, manufacturing and distribution that could not be adequately approached in the past. Now, optimization technology allows manufacturing companies to become more flexible and to more efficiently manage their supply chains by accounting for real life constraints and business rules. They can review “what-if” analyses of various scenarios, tied to key performance indicators that measure success on an ongoing basis. They can generate near optimal plans from the virtually infinite number of possible options. And with a clear set of future-oriented KPIs they can measure tomorrow’s performance before it happens.

In order to optimize, a supply chain management and optimization solution is required that is configured to account for the specific environment — machine capabilities and alternatives per product, production sequence including sequence-dependent changeovers, specific site constraints, inventory limitations, replenishment options, and so on. And it must be able to respond to changes in real time. The wrong answers can mean longer lead times, excess inventory, loss of business and lower profit. Keeping in mind that the aim of a business is to drive profit, executives have to ask where they can drive profit outside of their business’ primary function, and how they can improve their supply chain processes through optimization of the lean supply chain process.

The profit economy tactic examines the many intricate aspects of the manufacturing industry that can be refined and applies an optimization approach, tackling the challenges and leading to lower costs, more options, and ultimately, a better business and higher profits. For example, a manufacturer trying to schedule delivery of its products may use a diverse number of transportation methods, which may include rail, boat, road and air. This increases the complexity of on-time delivery and means the transportation scheduling team has to select the best possible mixture of modes accounting for total costs, delivery time and mileage.

Selecting just one possible solution isn’t good enough, and using ERP software for an insight into the historical solution isn’t going to help. And that’s just for delivery of a final product. Throw into the equation transporting raw materials between plants and scheduling the number of hours delivery teams can legally work, and you have a logistical headache that is costing companies millions of dollars every year. So why don’t the schedule planners have access to optimization solutions that offer more options?

Workforce planning is yet another area that’s ripe for optimization for manufacturing companies. Whether a company is overseeing, buyers of raw materials, workers on the production line, or delivery drivers, it needs to tie staffing to the busiest periods of activity, align skills to needs and account for constraints — be they legal, union or employee preferences. Many organizations, however, are unable to match labor supply with demand. They lack the forward-looking view that is crucial to eliminating every bit of waste from their operations.

Supply chain planning and optimization calls for a platform that embraces the end–to-end supply chain. To be sure, suppliers need to get products to customers on time — but they ought to be able to meet that goal with maximum efficiency at every step. For the manufacturing industry’s profit economy, “good enough” isn’t good enough. Businesses have become accustomed to a certain amount of inefficiency, but even a few percentage points of waste carry a price tag that few can afford. The algorithms and technology that make up a modern-day optimization solution can help to close that significant gap.