Browsing by Author "Larrain, Homero"

Now showing 1 - 5 of 5
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    A dynamic multi-plant lot-sizing and distribution problem
    (2016) Darvish, Maryam; Larrain, Homero; Coelho, Leandro C.
    In this paper, we investigate a multi-plant, production planning and distribution problem for the simultaneous optimisation of production, inventory control, demand allocation and distribution decisions. The objective of this rich problem is to satisfy the dynamic demand of customers while minimising the total cost of production, inventory and distribution. By solving the problem, we determine when the production needs to occur, how much has to be produced in each of the plants, how much has to be stored in each of the warehouses and how much needs to be delivered to each customer in each period. On a large real data-set inspired by a case obtained from an industrial partner, we show that the proposed integration is highly effective. Moreover, we study several trade-offs in a detailed sensitivity analysis. Our analyses indicate that the proposed scenarios give the company competitive advantage in terms of reduced total logistics cost, and also highlight more possibilities that become available taking advantage of an integrated approach towards logistics planning. These abundant opportunities are to be synergised and exploited in an interconnected open global logistics system.
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    Aircraft line maintenance scheduling and optimisation
    (2020) Shaukat, Syed; Katscher, Mathias; Wu, Cheng-Lung; Delgado, Felipe; Larrain, Homero
    With the advent of new technologies and more modern aircraft, many of the maintenance jobs traditionally scheduled for periodic block checks can now be performed in the "line maintenance" environment, i.e., during layovers between scheduled flights of an aircraft. This flexibility can be exploited to reduce maintenance costs and improve fleet utilisation of an airline. In this paper we introduce and study the Line Maintenance Scheduling Problem (LMSP). The LMSP assigns jobs to available maintenance opportunities, defined by aircraft routes, and sets the starting time for each job. Its objective is to minimise the deviation from this schedule with respect to given due dates for each task, without exceeding resource capacity at the airports at any moment. We formulate the LMSP as a mixed integer programming problem, and describe and compare two solution approaches for this problem: an integrated exact solution algorithm, which solves job assignment and timetabling simultaneously, and a sequential, heuristic approach. We tested our algorithms on a set of instances inspired on data provided by an industry partner. Our experiments show the applicability of both approaches on realistic settings: the exact approach was able to find the optimal solution for all instances, in less than 10 min on average. Our analysis also shows with an example that line maintenance can be more efficient when capacity is spatially spread, even if the total capacity is reduced.
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    Choosing the Right Express Services for Bus Corridor with Capacity Restrictions
    (SAGE PUBLICATIONS INC, 2010) Larrain, Homero; Giesen, Ricardo; Carlos Munoz, Juan
    In public transit systems with high demand levels, the use of express bus services that serve only a subset of stops along certain routes appears to be a promising alternative given the benefits that they offer to both users and operators. In practice, express services in systems such as Transmilenio (Bogota, Colombia), Transantiago (Santiago, Chile), and Metro Rapid (Los Angeles, California) have proved highly appealing. To determine what types of express services would be attractive on a bus corridor given the characteristics of its demand, four parameters are defined for identifying corridor demand profiles: the base load profile shape, the scale of demand, the demand imbalance between the outbound and inbound directions, and the average trip length. A series of indicators was also defined to measure the potential benefits of express services in the scenarios studied. The results of the experimental simulations show that a crucial parameter for determining the potential benefits of express services is the average trip length along the corridor. The incorporation of express services is particularly attractive in corridors with demand profiles that increase or decrease monotonically. In addition, the results suggest that in other cases, the complexity of the demand shape could allow for more complex express service patterns.
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    Design of limited-stop services for an urban bus corridor with capacity constraints
    (PERGAMON-ELSEVIER SCIENCE LTD, 2010) Leiva, Carola; Carlos Munoz, Juan; Giesen, Ricardo; Larrain, Homero
    In high-demand bus networks, limited-stop services promise benefits for both users and operators, and have proven their attractiveness in systems such as Transmilenio (Bogota, Colombia) and Transantiago (Santiago, Chile). The design of these services involves defining their itinerary, frequency and vehicle size, yet despite the importance of these factors for the network's efficiency, no published works appear to provide the tools for designing high-frequency unscheduled services on an urban bus corridor, minimizing social costs.
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    Optimizing the long-term costs of an Inventory Routing Problem using linear relaxation
    (2024) Chiu, Agustin; Angulo, Gustavo; Larrain, Homero
    The Inventory Routing Problem (IRP) arises in logistics operations when routing and inventory decisions are made simultaneously. In this work, some ideas to improve the long-term performance of the rolling horizon strategy are explored. First, three simple modifications to the IRP are tested to improve its long-term performance: using safety stocks, defining minimum inventory levels for the last period of the planning horizon, and using an artificial discount rate in the objective function. We use this improved IRP as a benchmark. Then, a solution strategy is proposed where an approximation is used in the final periods of the planning horizon, which is based on the linear relaxation of the IRP. The algorithm is calibrated and, through simulation, compared to the benchmark on a set of randomly generated instances with up to 30 customers, three vehicles, and 20 periods, and different costs and uncertainty levels. It is shown that the proposed algorithm is, on average, three times faster than the benchmark and generates savings between 1% and 2%. Under favorable conditions (low uncertainty, low inventory cost, and one vehicle), it can generate savings of around 10% in long-term costs.