Transport analytics in action: a cloud-based decision support system for efficient city bus transportation

Optimising city bus transport operations helps conserve fuel by providing the urban transport service as efficiently as possible. This study develops a Cloud-based Decision Support System (C-DSS) for transport analytics. The C-DSS is based on an intelligent model on location of depots for opening new depots and/or closing a few existing depots and allocation of city-buses to depots. The C-DSS is built on the Cloud Computing architecture with three layers and includes an efficient and simple greedy heuristic algorithm. Using modern information and communications technology tools, the proposed C-DSS minimizes the cost of city bus transport operations and in turn to reduce fuel consumption and CO2 emissions in urban passenger transport. The proposed C-DSS is demonstrated for its workability and evaluated for its performance on 25 large scale pseudo data generated based on the observation from Bangalore Metropolitan Transport Corporation (BMTC) in India

Minimizing total weighted tardiness on a batch-processing machine with non-agreeable release times and due dates

This study considers the scheduling problem observed in the burn-in operation of semiconductor final testing, where jobs are associated with release times, due dates, processing times, sizes, and non-agreeable release times and due dates. The burn-in oven is modeled as a batch-processing machine which can process a batch of several jobs as long as the total sizes of the jobs do not exceed the machine capacity and the processing time of a batch is equal to the longest time among all the jobs in the batch. Due to the importance of on-time delivery in semiconductor manufacturing, the objective measure of this problem is to minimize total weighted tardiness. We have formulated the scheduling problem into an integer linear programming model and empirically show its computational intractability. Due to the computational intractability, we propose a few simple greedy heuristic algorithms and meta-heuristic algorithm, simulated annealing (SA). A series of computational experiments are conducted to evaluate the performance of the proposed heuristic algorithms in comparison with exact solution on various small-size problem instances and in comparison with estimated optimal solution on various real-life large size problem instances. The computational results show that the SA algorithm, with initial solution obtained using our own proposed greedy heuristic algorithm, consistently finds a robust solution in a reasonable amount of computation time

Scheduling algorithms for heterogeneous batch processors with incompatible job-families

We consider the problem of scheduling heterogeneous batch processors (i.e., batch processors with different capacity) with incompatible job-families and non-identical job sizes to maximize the utilization of the batch processors. We analyzed the computational complexity of this problem and showed that it is NP-hard and proposed eight variants of a fast greedy heuristic. A series of computational experiments were carried out to compare the performance of the heuristics and showed that the heuristics are capable of consistently obtaining near (estimated) optimal solutions with very low-computational burden for large-scale problems. We also carried out a study to find the effect of family processing time changes on the performance of the heuristics. This sensitivity analysis indicated that the processing time set of job-families influences the performance of the heuristic algorithms

Heuristic algorithms for scheduling heat-treatment furnaces of steel casting industries

This paper addresses a research problem of scheduling parallel, nonidentical batch processors in the presence of dynamic job arrivals, incompatible job-families and non-identical job sizes.We were led to this problem through a realworld application involving the scheduling of heat-treatment operations of steel casting. The scheduling of furnaces for heat-treatment of castings is of considerable interest as a large proportion of the total production time is the processing times of these operations. In view of the computational intractability of this type of problem, a few heuristic algorithms have been designed for maximizing the utilization of heat-treatment furnaces of steel casting manufacturing. Extensive computational experiments were carried out to compare the performance of the heuristics with the estimated optimal value (using theWeibull technique) and for relative effectiveness among the heuristics. Further, the computational experiments show that the heuristic algorithms proposed in this paper are capable of obtaining near (statistically estimated) optimal utilization of heat-treatment furnaces and are also capable of solving any large size real-life problems with a relatively low computational effort

Promising Combination Systemic Fungicides in Combating Basal Stem Rot Disease of Coconut

Basal stem rot disease is the most challenging disease in coconut crop, caused by Ganoderma lucidum. Combating the disease with new generation fungicides is a viable strategy for the promising disease control. Single and combination of new systemic fungicides in different commercial formulations were tested against the Ganoderma lucidum. Under in vitro study at 100, 250 and 500 ppm concentrations. The results revealed that Hexaconazole 4% + Carbendazim 16% SC, Hexaconazole 5% + Validamycin 2.5%SC and Azoxystrobin 11% + Tebuconazole 18.3% SC W/W were found superior in inhibiting the mycelial growth of Ganoderma as compared to other fungicides. Per cent inhibition indicated the effectiveness of potent fungicides against the pathogen even at lower concentration

Ganoderma wilt – A Lethal Disease of Coconut in Tamil Nadu Research Accomplishments and Future Thrust

Ganoderma wilt or Thanjavur wilt disease is the most lethal one, is caused by the fungus Ganoderma lucidum (leys) Karst and it is of major limiting factor in coconut production in nine coastal districts of Tamil Nadu. The high alarming of the disease alerted the government to launch the Ganoderma wilt research in the state in the yesteryear. Subsequently, more than five decadal researches done on this disease that provides preliminary, applied and advanced results and outcomes that are crucial and fruitful in the  disease management. The endemic nature of the disease is evident and it has been witnessed with the severe spread of the disease in the east coast region of Tamil Nadu after the attack of Gaja cyclone urges the research efforts to contain the disease. The disease incidence ranges from 6.5 % to 50% in Thanjavur district followed by Nagapattinam and Thiruvarur districts is continuously reminds the threat of the disease to the coconut farmers in this region. In this juncture, It is indispensable to highlight the significant works on  documentation of disease incidence, isolation of pathogen , pathogenicity, virulence study, disease index formula development,  early and rapid detection methods, epidemiology, pathophysiology, agronomical, cultural, biological chemical disease control methods ,integrated  disease management  strategy etc., .done ,in the past  and it is  necessarily a boon to the current research work. Obviously, the brief review will make a corner stone and open up new discussion on the most important aspects of the disease management. This necessitates and leads the new line of research coping with the future thrusts will helpful in combating the lethal disease in the post Gaja cyclone scenario in the state