Minimizing the sum of flow times with batching and delivery in a supply chain

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The aim of this thesis is to study one of the classical scheduling objectives that is of minimizing the sum of flow times, in the context of a supply chain network. We consider the situation that a supplier schedules a set of jobs for delivery in batches to several manufacturers, who in tum have to schedule and deliver jobs in batches to several customers. The individual problem from the viewpoint of supplier and manufacturers will be considered separately. The decision problem faced by the supplier is that of minimizing the sum of flow time and delivery cost of a set of jobs to be processed on a single machine for delivery in batches to manufacturers. The problem from the viewpoint of manufacturer is similar to the supplier's problem and the only difference is that the scheduling, batching and delivery decisions made by the supplier define a release date for each job, before which the manufacturer cannot start the processing of that job. Also a combined problem in the light of cooperation between the supplier and manufacturer will be considered. The objective of the combined problem is to find the best scheduling, batching, and delivery decisions that benefit the entire system including the supplier and manufacturer. Structural properties of each problem are investigated and used to devise a branch and bound solution scheme. Computational experience shows significant improvements over existing algorithms and also shows that cooperation between a supplier and a manufacturer reduces the total system cost of up to 12.35%, while theoretically the reduction of up to 20% can be achieved for special cases

Designing and Implementation of Fuzzy Case-based Reasoning System on Android Platform Using Electronic Discharge Summary of Patients with Chronic Kidney Diseases

Introduction: Case-based reasoning (CBR) systems are one of the effective methods to find the nearest solution to the current problems. These systems are used in various spheres as well as industry, business, and economy. The medical field is not an exception in this regard, and these systems are nowadays used in the various aspects of diagnosis and treatment. Methodology: In this study, the effective parameters were first extracted from the structured discharge summary prepared for patients with chronic kidney diseases based on data mining method. Then, through holding a meeting with experts in nephrology and using data mining methods, the weights of the parameters were extracted. Finally, fuzzy system has been employed in order to compare the similarities of current case and previous cases, and the system was implemented on the Android platform. Discussion: The data on electronic discharge records of patients with chronic kidney diseases were entered into the system. The measure of similarity was assessed using the algorithm provided in the system, and then compared with other known methods in CBR systems. Conclusion: Developing Clinical fuzzy CBR system used in Knowledge management framework for registering specific therapeutic methods , Knowledge sharing environment for experts in a specific domain and Powerful tools at the point of care

Identifying the critical success factors of organization with Analytic Hierarchy Process approach (case study – Iran Argham Company)

In today’s challenging and complex world, organizations success depends on productivity, continuous improvement in all dimensions and reforming the pattern of resource utilization. Therefore, organizations, while considering restrictions, should focus on the most effective factors or so-called critical success factors. This paper intends to identify and prioritize the critical success factors, among other, factors influencing success of the organization, using hierarchical analysis and application of tools and related software. Analytic Hierarchy Process provides the possibility to compare the factors via creating matrix of paired comparisons. The case study in this research includes identifying the critical success factors and prioritizing them in Iran Argham Company. Finally, among the results presented, five critical success factors are identified from the forty influential factors. These five factors account for about seventy percent of the organization’s success. It should be noted that most studies conducted in this area focuse on the certain processes and special systems rather than study on the organization as a whole unit. This model can also be generalized to all organizations, including SMEs, and would provide remarkably valuable approaches, especially in competitive markets. Keywords: key success factors, strategic management, critical success factors, AHP. JEL Classification: M10, M14, L21, C4

Minimizing the sum of flow times with batching and delivery in a supply chain

The aim of this thesis is to study one of the classical scheduling objectives that is of minimizing the sum of flow times, in the context of a supply chain network. We consider the situation that a supplier schedules a set of jobs for delivery in batches to several manufacturers, who in tum have to schedule and deliver jobs in batches to several customers. The individual problem from the viewpoint of supplier and manufacturers will be considered separately. The decision problem faced by the supplier is that of minimizing the sum of flow time and delivery cost of a set of jobs to be processed on a single machine for delivery in batches to manufacturers. The problem from the viewpoint of manufacturer is similar to the supplier's problem and the only difference is that the scheduling, batching and delivery decisions made by the supplier define a release date for each job, before which the manufacturer cannot start the processing of that job. Also a combined problem in the light of cooperation between the supplier and manufacturer will be considered. The objective of the combined problem is to find the best scheduling, batching, and delivery decisions that benefit the entire system including the supplier and manufacturer. Structural properties of each problem are investigated and used to devise a branch and bound solution scheme. Computational experience shows significant improvements over existing algorithms and also shows that cooperation between a supplier and a manufacturer reduces the total system cost of up to 12.35%, while theoretically the reduction of up to 20% can be achieved for special cases.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A TWO-STAGE GREEDY HEURISTIC FOR A FLOWSHOP SCHEDULING PROBLEM UNDER TIME-OF-USE ELECTRICITY TARIFFS

This paper studies a two-machine flowshop scheduling problem under time-dependent electricity tariffs, in which electricity prices may vary from time to time throughout the day. The main issue is to assign a set of jobs to available time slots with different electricity prices to minimise the total resource cost required for processing the jobs. The main contribution of this work is two-fold. First, a new continuous-time mixed-integer linear programming (MILP) model is proposed for the problem. Second, a two-stage greedy heuristic is developed. A computational experiment on randomly generated instances demonstrates that the greedy algorithm can improve the objective function by almost 40 percent. The algorithm can be applied by production managers to scheduling jobs in a flowshop under time-of-use (TOU) electricity tariffs to save electricity costs

Applying data mining techniques to determine important parameters in chronic kidney disease and the relations of these parameters to each other.

Introduction: Chronic kidney disease (CKD) includes a wide range of pathophysiological processes which will be observed along with abnormal function of kidneys and progressive decrease in glomerular filtration rate (GFR). According to the definition decreasing GFR must have been present for at least three months. CKD will eventually result in end-stage kidney disease. In this process different factors play role and finding the relations between effective parameters in this regard can help to prevent or slow progression of this disease. There are always a lot of data being collected from the patients' medical records. This huge array of data can be considered a valuable source for analyzing, exploring and discovering information. Objectives: Using the data mining techniques, the present study tries to specify the effective parameters and also aims to determine their relations with each other in Iranian patients with CKD. Material and Methods: The study population includes 31996 patients with CKD. First, all of the data is registered in the database. Then data mining tools were used to find the hidden rules and relationships between parameters in collected data. Results: After data cleaning based on CRISP-DM (Cross Industry Standard Process for Data Mining) methodology and running mining algorithms on the data in the database the relationships between the effective parameters was specified. Conclusion: This study was done using the data mining method pertaining to the effective factors on patients with CKD

Combination therapy with everolimus and tacrolimus in kidney transplantation recipients: A systematic review

Background and aims: Immunosuppressive regimens are a key component for successful kidney transplantation. This systematic review aimed to assess the efficacy and safety of combination therapy of everolimus with tacrolimus in kidney transplantation recipients. Methods: Results were limited to English-language articles. Trials where recipients received another regimen were excluded. The Cochrane Central Register of Controlled Trials and MEDLINE were searched via the optimally sensitive strategies for the identification of randomized trials, combined with the following MeSH headings and text words: Everolimus, Certican, Zortress, tacrolimus, prograf, and kidney transplantation. Results: Five relevant studies of everolimus in combination with tacrolimus were identified and results of them were interpreted. Two trials investigated Fix dose of everolimus in combination with low (1.5-3 mg) versus standard dose of tacrolimus (4-7 mg). One trial investigated variable doses of everolimus (1.5 mg/day or 3 mg/day) in combination with fix dose of tacrolimusand two trials compared fix dose of everolimus versus reduction or elimination of tacrolimus. Sample size of RCTs ranged from 20 to 398 and the follow up time ranged from six to 24 months. The quality score on the Jadad score was 3 in all five trials indicating moderate quality. Conclusion: Immune suppressive regimens including everolimus in combination with tacrolimus therapy show better safety and efficacy compared with single-mode but these differences were not significant in overall studies. In general, compared with a regimen without combination of everolimus with tacrolimus, the newer immunosuppressive regimen consistently reduced the incidence of short-term biopsy-proven acute rejection. However, evidence about impact on side-effects, long term graft loss, compliance and overall health-related quality of life is limited