Optimal Daily Scheduling Research Articles

Incorporation of Within-Season Yield Growth into a Mathematical Programming Sugarcane Harvest Scheduling Model

AbstractThis study focuses on the development of a optimal harvest scheduling mathematical programming model which incorporates within-season changes in perennial crop yields. Daily crop yield prediction models are estimated econometrically for major commercially grown sugarcane cultivars. This information is incorporated into a farm-level harvest scheduling linear programming model. The harvest scheduling model solves for an optimal daily harvest schedule which maximizes whole farm net returns above harvesting costs. Model results are compared for a commercial sugarcane farm in Louisiana.

EXPLORE—Hybrid Expert System for Water Networks Management

A hybrid expert system called EXPLORE has been developed to manage the Seville City water-supply system. The main difficulties are the lack of information on management procedures, the complicated electrical tariff, the variability of the water network topology, and the dependency of the water demands, which is a major uncontrollable factor. EXPLORE reduces the cost of the operation of pumping the water to the different storage tanks. For this task EXPLORE employs the water demand forecast to obtain an optimal daily pumping schedule. EXPLORE has several additional benefits, in that it allows the collection of the operator's experience and the refinement of the operation processes through the simulation of new strategies, and it provides adequate training for new operators. The system has been applied to the management of the Seville City water-supply system. A prototype has been tested and has provided great improvement in the electrical costs (a savings of 25% over the current operation).

EORTC phase II study of daily oral linomide in metastatic renal cell carcinoma patients with good prognostic factors

Following a previous EORTC GU-Group study, in which linomide showed some activity in poor prognosis patients, this study was initiated to determine the effect of linomide in more favourable patients. 35 patients with metastatic renal cell carcinoma with good prognostic factors, i.e. good performance status, prior nephrectomy, no prior systemic therapy, and no liver, bone or brain metastases, were treated with linomide, a quinoline derivative with immunomodulating properties, at a dose of 10 mg daily, after an initial dose escalation during the first 4 weeks of treatment. In 29 evaluable patients, no responses were observed (95% confidence interval 0–10%). Best overall response was no change in 9 patients, for a median duration of 4 months. Linomide in this schedule was poorly tolerated, with 17% (6 patients) of patients being withdrawn and 23% (8 patients) having dose reductions due to adverse events, mostly influenza-like symptoms of myalgia, arthralgia and fatigue. Several cases of pericarditis and neuropathy were observed. In spite of selection of favourable prognosis patients and an optimal daily dosing schedule, linomide was not an effective treatment in renal cell carcinoma. In view of toxicity and lack of efficacy, there is no rationale in further testing the drug in this disease.

新しい非ステロイド性抗炎症薬ＵＨＡＣ６２カプセルの投与方法に関する検討

A double-blind comparative study among 9 medical centers was conducted in order to investigate the optimal daily administration schedule of UHAC62 (Generic name: Meloxicam), a kind of non-steroidal anti-inflammatory oxycam agent. The daily 10 mg of UHAC62, which had been considered as an optimal dose, was administered either once daily, immediately after supper (Group O), or given twice a day divided into 5 mg immediately after breakfast and supper (Group T), both for weeks to patients with rheumatoid arthritis.Out of the total 52 patients, 1 patient was excluded from the analyses; and 41 patients (Group O: 23 cases, Group T: 18 cases), 51 patients (Group O: 27 cases, Group T: 24 cases) and 44 patients (Group O: 24 cases, Group T: 20 cases) were subjected to the ratings of Final Global Improvement, Overall Safety, and Usefulness, respectively. The results showed the following:(1) The ratio of the patients who showed a better than “Moderate Improvement” in the Final Global Improvement Rating was 30.4 % and 27.8 % in the Group O and Group T, respectively.(2) The ratio of the patients on whom the test drug was shown to be “Completely Safe” in the Overall Safety Rating was 88.9% and 91.7% in the Group O and Group T, respectively. All of the adverse drug reactions which were seen in the patients of Group O and the 2 patients of the Group T were assessed as “mild”.(3) The ratio of the patients on whom the test drug was rated as better than “Useful” was 29.2% and 25.0 % in the Group O and Group T, respectively.There was no significant difference in the overall evaluations and the improvement rating of the symptoms between the groups.According to these results, it was considered that the once daily administration of UHAC62 might be more promising for materializing a higher compliance in the patients who need long-term administration, although both regimens, the once and the twice daily administrations are applicable.

Optimization of Water Supply System Operation

An optimization model has been developed to generate pump schedules in real-time operation for a complex water supply system by considering major difficulties posed by a complicated tariff; especially demand charges, discrete pump discharges, and other physical constraints. The model decomposes in space and time the system into several subsystems, and planning periods into operational periods. Progressive optimality is applied to solve a dynamic programming model. The pump discharges are discretized and arranged by heuristic methods in order to reduce the number of times pumps are switched on. In real-time operation, billing monthly demand is estimated by a long-term model and then incorporated in a short-term model to obtain an optimal daily schedule in a relatively short computational time. Application is made to the city of Pittsburgh's water supply system. To implement the model in making operational decisions, a computer software package is also coded. A simulation run on part of the system in a test year shows that the optimal solution could have saved 20% of the actual cost.

A Multiple Objective Model for a Just‐in‐Time Manufacturing System Environment

Presents a linear goal programming (LGP) model, which can be used to derive an optimal daily production schedule for JIT production systems. Also provides an explanation of how a detailed post‐optimal LGP analysis can enable a decision maker to examine the effects of production scheduling in a JIT “mixed‐model” production environment. To illustrate the informational efficacy of the proposed JIT‐based LGP model, presents an illustrative example.

Optimal daily scheduling of cascaded plants using a new algorithm of nonlinear minimum cost network flow

An optimality condition theorem and an algorithm for nonlinear minimum-cost network flow are proposed. A computational network model for optimal daily scheduling of cascaded plants (ODSCP) is established, and an algorithm for searching the minimum-cost flow-augmenting path and the maximum-cost flow-reducing path in the computational network model of ODSCP is described. Digital computations are carried out and the results show that the proposed method is very fast compared to existing methods. >

Short-Term Scheduling of a Large Hydroelectric Power System

The Norwegian electrical power production system of installed capacity - 20 GW is 99.5 % hydroelectric and widely dispersed geographically. The State Power System.(SPS) is the owner of - 30%. of the electric production system and - 90%. of the main grid system which for the most part is made up of 300- and 420 kV lines. The paper deals with the optimal daily scheduling of SPS's dominant share of the Norwegian electrical production resources. Following an overview of the overall scheduling problem, the presentation reports on each defined main sublevel of analysis in terms of problem formulation, method of analysis, special problems and sample results.

Recent Advances Concerning the Problem of Optimal Daily Scheduling of Electricity Production in Hungary

This paper is concerned with the problem of optimal daily scheduling of the electricity production by power system of thermal power plants. The problem and its model is closely related to the so called optimal unit commitment problems. The main difference is that in our approach the transmission network is also taken into account. Beside the variables and constraints describing the production of the individual power plants there are also variables characterizing the state of the network. The constraints imposed bv the transmission system and the active power losses are also taken into consideration. A further difference is in the way in which we deal with the units of the power stations. Instead of the operation of single units we take always the feasible combined operations of the units of a power station into account. Time-dependent stillstand and restart costs are involved. A special type of constraint appearing in our problem is the so-called fuel constraint. This requires that in some power plants the daily overall production - directly connected with fuel consumption - should differ from a given value only to the extent of a very small percentage.

Layered Network Model Approach to Optimal Daily Hydro Scheduling

The objective of daily hydroelectric scheduling is to generate power as much as possible in accordance with changes in electricity demand under highly constrained conditions. A highly efficient layered network model is proposed and applied to the Kiso river hydroelectric system, which is one of the most complicated hydropower systems in Japan. First, the practicality of the proposed model is demonstrated by its ability to cope with power increases at peak demand periods, and second by the easy handring of its major operational constraints and objectives.

Layered Network Model Approach to Optimal Daily Hydro Scheduling

The objective of daily hydroelectric scheduling is to generate power as much as possible in accordance with changes in electricity demand under highly constrained conditions. A highly efficient layered network model is proposed and applied to the Kiso river hydroelectric system, which is one of the most complicated hydropower systems in Japan. First, the practicality of the proposed model is demonstrated by its ability to cope with power increases at peak demand periods, and second by the easy handring of its major operational constraints and objectives.