PALMA INFANTE, CRISTIAN DERECK
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PALMA INFANTE, CRISTIAN DERECK
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cristianpalma@udd.cl
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22941755100

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Multiperiod Optimisation of Irrigated Crops under Different Conditions of Water Availability

2018 , Mathias Kuschel-Otárola , Diego Rivera Salazar , Eduardo Holzapfel , PALMA INFANTE, CRISTIAN DERECK , GODOY FAUNDEZ, ALEX ORIEL

We propose a nonlinear optimisation model which maximises profits by resource allocation on a monthly time scale, considering a monthly crop yield model. The proposed model was applied to six management scenarios (two seasonal and four monthly), nine conditions of water availability, and two situations of resource availability under Chilean conditions. These situations provided the same seasonal amount of resources, but different distributions over time. The model included improvements in water resource management such as water storage and water transactions, being the latter a monthly decision variable that can increase farmers’ profits. According to our results, monthly scenarios gave high profits, even better with appropriate resource distribution. When water costs are high, water transactions allow loss reduction of up to 50%. Regarding labour, the lack of availability is more critical than the wages.

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A comparison of optimization models for lumber production planning

2015 , Francisco P Vergara , PALMA INFANTE, CRISTIAN DERECK , Héctor Sepúlveda

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An integrated multi-criteria decision analysis and optimization modeling approach to spatially operational road repair decisions

2021 , Sättar Ezzati , PALMA INFANTE, CRISTIAN DERECK , Pete Bettinger , Ljusk Ola Eriksson , Anjali Awasthi

In this study, we developed a generic cost-effective approach for spatially explicit decision support involving the allocation of road repair treatments. The approach begins with an assessment of the existing road condition to identify the extent of environmental impacts and to determine road repair regimes in a subjective manner using group-decision making efforts. An integer programming model is then formulated by combining expert opinions with operational costs to guide repair schedules required for each road segment at the operational planning level. To demonstrate model performance, we applied it to a 400 km2 landscape consisting of 289 km of paved roads in the mountainous region of the Hyrcanian forests in Iran. We assessed sensitivity of the inputs, such as weight verification, budgetary limitations, and rehabilitation weights. The results of the subjective analysis show that 76% of the roads analyzed in these forests must be prioritized to receive treatments as intended for logistical purposes. Incorporating the extent of environmental dimensions into operational costs allows us to generate an optimal tradeoff curve by selecting an appropriate treatment for segments of a road network. The approach demonstrated here can be used to design detailed alternative solutions for addressing spatially-informed road decisions under various terrain conditions.

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A Robust Model for Protecting Road-Building and Harvest-Scheduling Decisions from Timber Estimate Errors

2014 , PALMA INFANTE, CRISTIAN DERECK , John D. Nelson

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Modeling Lean and Agile Approaches: A Western Canadian Forest Company Case Study

2018 , Francisco Vergara , PALMA INFANTE, CRISTIAN DERECK , John Nelson

In the forest supply chain of the coast of British Columbia, the material flows are directed toward the push production of commodity products. This industry has not adopted lean and agile principles due to unclear economic impacts on the supply chain in changing market conditions. We tested the ability of lean and agile principles to improve performance in the coastal integrated forest industry. Mixed integer programming formulations were subject to over–under production capacity, and over–under demand fulfillment penalties to emulate agile, lean, and hybrid manufacturing environments, when solving the planning problem. Assuming that the coastal integrated forest industry performs as a hybrid environment, the profit results of each manufacturing environment were judged. The results show that, opportunities for profit improvement were 11% for adopting an agile environment when demand was stable with low variation and large batches of production. However, profit improvement was non-existent when the same demand attributes apply but with high variation. The opportunities for profit improvement were 12% when an agile environment or lean environment was adopted when demand was stable with low variation and small batches of production. However, opportunities for profit improvements of 15% existed for adopting an agile environment when demand was unstable with high variation and small batches of production.

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CHARACTERIZATION OF ROBUST SOLUTIONS OF MULTI-OBJECTIVE OPTIMIZATION MODELS WITH UNCERTAIN WEIGHTS: APPLICATION IN A SAWMILL

2018 , PALMA INFANTE, CRISTIAN DERECK

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Drinking water and urban growth: analysis of the integration of the land-use and water supply planning instruments in BioBio Region, Chile

2017 , PALMA INFANTE, CRISTIAN DERECK , GONZALEZ MATHIESEN, MARIA CONSTANZA , Richard Zapata , César Jara

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Considering Section Balance in an Integer Optimization Model for the Curriculum-Based Course Timetabling Problem

2020 , PALMA INFANTE, CRISTIAN DERECK , Patrick Bornhardt

University course timetabling is a complex and time-consuming duty that every educational institution faces regularly. It consists of scheduling a set of lectures in predefined time slots so as to avoid student conflicts, meet teacher and room availability, and manage several institution-specific operational rules. In this paper, we schedule courses based on a curriculum, that is, before the students’ registration. Unlike other curriculum-based models, the proposed model considers two practical aspects when managing the conflicts between lectures: (i) it schedules sections of subjects so that each section is evenly likely to be registered by the students, and (ii) it considers the failure rates and periodicity a subject is taught. We present a multi-objective integer programming model that maximizes the use of specific time slots, the symmetry in which the lectures of a course are scheduled during a week, and the flexibility for straggler students to take courses. The model is solved using commercial software, and it is applied to a real course-timetabling problem. We show the advantages of its use by comparing the model’s solution with the actual solution obtained by the manual scheduling.

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Impact of Timber Volume and Grade Estimation Error on the British Columbia Coastal Supply Chain

2016 , PALMA INFANTE, CRISTIAN DERECK

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Assessing the effectiveness of static heuristics for scheduling lumber orders in the sawmilling production process

2024 , Francisco Vergara , PALMA INFANTE, CRISTIAN DERECK , John D. Nelson

Although optimization models can be used to plan the production process, in most cases static heuristics, such as earliest due date (E), longest processing time (L), and shortest processing time (S), are used because of their simplicity. This study aims to analyze the production cost of the static heuristics and to determine how this cost relates to the size of the production orders in the sawmilling industry. We set a planning problem with different orders and due dates and solved it using two cost-minimization models to compare their solutions. The first was a planning model (PL) where orders were split up into products demand by period, and the second, a planning scheduling (PS) where the sequence of processing orders based on static heuristics was assumed as known. In the latter, the minimum production cost for each static heuristic was found. In both models, the same resource constraints were assumed. The costs showed no significant changes based on order sizes. However, 0,5 % of orders were delayed using PS-E, and 17 % of orders were delayed using PL. PL was an efficient solution method when changing the orders´ size and when looking for the best static heuristic to process the orders. However, PS-E showed the ability to reduce the backlog close to zero while the PL backlog ratio was 17 %. No penalties were applied to backlogs due to their subjective nature; however, when shortages occurred, the demand was unmet or backlogged with substantial costs. Thus, in case the proposed method is adopted using a conservative backlog cost, a sawmill producing under the cut-to-order environment that produces 300000 m3 /year would reduce backlogged orders by 51000 m3. If the holding lumber cost is 2 $/m3, annual savings would be $408000.

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