Comparison of modeling approaches for evaluation of machine fleets in central Sweden forest operations

There are many factors to consider when deciding which technologies to use in forest operations and how to plan their use. One important factor is the overall cost when choosing between the established two-machine system (TMS) with a harvester and a forwarder, and a one-machine system with a harwarder in final fellings. Such considerations can be done with different model approaches, all of which have their strengths and weaknesses. The aim of this study was to analyze and compare the TMS and harwarder potential using a Detailed Optimization (DO) approach and an Aggregated Heuristic (AH) approach. The main differences are the aggregation of seasons, including machine system teams, and spatial considerations. The analyses were done for one full year of final fellings for a large forest company's region in central Sweden, containing information necessary for calculating costs for logging, relocation between stands and traveling between the operator's home bases and the stands. The approaches were tested for two scenarios; when only TMS were available, and when both TMS and harwarders were available. The main results were that the approaches coincided well in both potential to decrease total costs when harwarders where available, and distribution of TMS and harwarders. There were some differences in the results, which can be explained by differences in thecalculation approach. It was concluded that the DO approach is more suitable when detailed analyses are prioritized, and the AH approach is more suitable when a more approximate analysis will suffice or the available resources for making the analysis are more limited

Refinery production planning : model and solution method

In this paper we present a general model and solution approach for refinery process planning. The model is nonlinear and has a flexible description to account for different configurations at a refinery. The solution approach is based on solving the nonlinear model directly with a commercial solver. Since the model is highly nonlinear we apply a special procedure to find a good starting solution. We test standard commercial nonlinear solvers on a set of standard test examples

Simulation of production and sales planning in refinery operations

In this paper we discuss some computational experiments on simulating refinery operations. We compare an integrated approach with recursively solving a production planning and sales planning problem. We test two different descriptions of the demand behaviour. The first is based on a fixed lower and upper limit and the second on a demand that varies with the product price. We also test the impact of different number of time periods in the planning horizon. We simulate the behaviour when detailed information of the demand is available

Simulation of production and sales planning in refinery operations

In this paper we discuss some computational experiments on simulating refinery operations. We compare an integrated approach with recursively solving a production planning and sales planning problem. We test two different descriptions of the demand behaviour. The first is based on a fixed lower and upper limit and the second on a demand that varies with the product price. We also test the impact of different number of time periods in the planning horizon. We simulate the behaviour when detailed information of the demand is available

A hybrid method based on linear programming and tabu search for routing of logging trucks

In this paper, we consider an operational routing problem to decide the daily routes of logging trucks in forestry. The industrial problem is difficult and includes aspects such as pickup and delivery with split pickups, multiple products, time windows, several time periods, multiple depots, driver changes and a heterogeneous truck fleet. In addition, the problem size is large and the solution time limited. We describe a two-phase solution approach which transforms the problem into a vehicle routing problem with time windows. In the first phase, we solve an LP problem in order to find a destination of flow from supply points to demand points. Based on this solution, we create transport nodes each of which defines the origin(s) and destination for a full truckload. In phase two, we make use of a standard tabu search method to combine these transport nodes, which can be considered to be customers in vehicle routing problems, into actual routes. The standard tabu search method is extended to consider some new features. The solution approach is implemented as part of a newly developed decision support system and we report on tests made on a set of industrial cases from major forest companies in Sweden

Optimized on-line process control of bleaching operations with OptCab

To produce pulp for paper production or as market pulp is a complicated on-line process with many integrated stages that impact the final quality. In the bleaching plant which is at the end of pulp production, the main objective is to increase pulp brightness within specified limits. Here chemical treatments are applied in sequential stages to achieve the right brightness while striving to maintain the pulp strength as unaffected as possible. The raw material, i.e. pulp logs and wood chips from saw mills, differ in quality and properties. Due to this, it is important to continuously update the amount of chemicals added to the pulp in real-time. This is typically done by experienced operators. In this paper, we describe an on-line optimization based decision support system called OptCab that controls the bleaching process at Billerud AB's paper mill in Skärblacka. The solution approach is based on two phases. In phase one, we establish approximations of each of the processes based on process data collected on-line. These approximations are found by solving a set of constrained least square problems and are updated every 15 minutes. In phase two, we formulate an overall nonlinear control problem that links all stages together and aims to minimize the cost of chemicals. This is solved on-line every five minutes. The system has been in operation during the last three years providing a 10% reduction in the use of chemicals. Additional benefits include a more stable brightness quality

Refinery optimization platform : a user’s manual : version 1.0

This is a manual for the Refinery Optimization Platform ROP which is a flexible platform for studying refinery production planning. The user can model the overall refining process in a multiperiodic setting, with linear and nonlinear representation of the refinery processes. All input and output is communicated via Excel sheet, where the user can define a general refining process together with required output reports. ROP enables the user to study the planning problem by experimenting with alternative modeling approaches and restrictions. A case study with input data and results is presented

RuttOpt : a decision support system for routing of logging trucks

We describe the decision support system RuttOpt, which is developed for scheduling logging trucks in the Swedish forest industry. The system is made up of a number of modules. One module is the Swedish road database NVDB which consists of detailed information of all the roads in Sweden. This also includes a tool to compute distances between locations. A second module is an optimization routine that finds a schedule i.e. set of routes for all trucks. This is based on a two phase algorithm where Linear Programming and a standard tabu search method are used. A third module is a database, storing all relevant information. At the heart of the system is a user interface where information and results can be viewed on maps, Gantt schedules and result reports. We also describe the characteristics of the general routing problem in forestry together with a focus on the planning process and systems in use in the Swedish situation. The system RuttOpt has been used in a number of case studies and we describe four of these. The case studies have been made in both forest companies and hauling companies. The cases range from ten to 110 trucks and with a planning horizon ranging from between one and five days. The results show that the system can be used to solve large case studies and that the potential savings are in the range 5-30%