Abstract
This research developed a solution approach that is a combination of a web application and the modified differential evolution (MDE) algorithm, aimed at solving a real-time transportation problem. A case study involving an inbound transportation problem in a company that has to plan the direct shipping of a finished product to be collected at the depot where the vehicles are located is presented. In the newly designed transportation plan, a vehicle will go to pick up the raw material required by a certain production plant from the supplier to deliver to the production plant in a manner that aims to reduce the transportation costs for the whole system. The reoptimized routing is executed when new information is found. The information that is updated is obtained from the web application and the reoptimization process is executed using the MDE algorithm developed to provide the solution to the problem. Generally, the original DE comprises of four steps: (1) randomly building the initial set of the solution, (2) executing the mutation process, (3) executing the recombination process, and (4) executing the selection process. Originally, for the selection process in DE, the algorithm accepted only the better solution, but in this paper, four new selection formulas are presented that can accept a solution that is worse than the current best solution. The formula is used to increase the possibility of escaping from the local optimal solution. The computational results show that the MDE outperformed the original DE in all tested instances. The benefit of using real-time decision-making is that it can increase the company’s profit by 5.90% to 6.42%.
Highlights
The Internet of Things, cloud technology, big data, and web and mobile applications are technologies used to increase the efficiency of the supply, production, and transportation chains.They allow for the application of information technology (IT) to current management knowledge
We apply an IT system that supports a company’s transportation planning so that the depot will send vehicles to pick up finished goods from production plants, and sometimes the depot has to send trucks to pick up raw materials from suppliers and deliver them to production plants
The casetoofbe increased profit, new demand for rawplan material from supplier) is updated from the production plants. This the new transportation will be sentthe to drivers using the web application, but if the profit is not information willwill be not transferred to the depot, which will use the proposed method to solve the increased, drivers be informed, and they will continue driving according to their current plan
Summary
The Internet of Things, cloud technology, big data, and web and mobile applications are technologies used to increase the efficiency of the supply, production, and transportation chains. At the beginning of the period, all pickup and delivery transportation will for decision-makers to use as planning the data for reoptimizing the transportation plan comesplans during thebe given toperiod the truck drivers Thethe trucks will get the information a information for decision-makers to use as the data for reoptimizing the transportation plan comes new route if they need to change their destination when they arrive at their current destination. The casetoofbe increased profit, new demand for rawplan material from supplier) is updated from the production plants This the new transportation will be sentthe to drivers using the web application, but if the profit is not information willwill be not transferred to the depot, which will use the proposed method to solve the increased, drivers be informed, and they will continue driving according to their current plan.
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