Novel Strategies for Heterocyclic Constructions via 1, 4-Dipolar Intermediates

In the thesis entitled " Novel Strategies for Heterocyclic Constructions via 1 ,4-Dipolar Intermediates"Synthesis of a complex organic molecules essentially involves the formation of carbon-carbon and carbon-heteroatom bonds. Various synthetic methods are available for these processes involving ionic, pericyclic and radical reactions. Among the pericyclic reactions, dipolar cycloaddition reactions, introduced by Huisgen, have emerged as a very powerful tool for heterocyclic construction. Heterocyclic compounds remain an important class of organic molecules due to their natural abundance and remarkable biological activity, thus constituting an intergral part of pharmaceutical industry. In this respect, developing newer synthetic methodology for heterocyclic construction has been an area of immense interest. In recent years, 1,3-dipolar cycloaddition reactions proved to be efficient routes to a wide variety of five membered heterocycles, as attested by their application in the total synthesis of various complex organic molecules. However, the potential application of similar 1,4- dipolar cycloaddition reactions for the construction of six memebered heterocycles remained underexploited. In this context, a systematic investigation of the reactivity of 1,4-dipoles generated from nitrogen heterocycles (pyridine and its analogues) and dimethyl acetylenedicarboxy!ate (DMAD) towards various dipolarophiles has been carried out and the results are embodied.

Multi-objective assembly job shop scheduling using genetic algorithm and tabu search

Assembly job shop scheduling problem (AJSP) is one of the most complicated combinatorial optimization problem that involves simultaneously scheduling the processing and assembly operations of complex structured products. The problem becomes even more complicated if a combination of two or more optimization criteria is considered. This thesis addresses an assembly job shop scheduling problem with multiple objectives. The objectives considered are to simultaneously minimizing makespan and total tardiness. In this thesis, two approaches viz., weighted approach and Pareto approach are used for solving the problem. However, it is quite difficult to achieve an optimal solution to this problem with traditional optimization approaches owing to the high computational complexity. Two metaheuristic techniques namely, genetic algorithm and tabu search are investigated in this thesis for solving the multiobjective assembly job shop scheduling problems. Three algorithms based on the two metaheuristic techniques for weighted approach and Pareto approach are proposed for the multi-objective assembly job shop scheduling problem (MOAJSP). A new pairing mechanism is developed for crossover operation in genetic algorithm which leads to improved solutions and faster convergence. The performances of the proposed algorithms are evaluated through a set of test problems and the results are reported. The results reveal that the proposed algorithms based on weighted approach are feasible and effective for solving MOAJSP instances according to the weight assigned to each objective criterion and the proposed algorithms based on Pareto approach are capable of producing a number of good Pareto optimal scheduling plans for MOAJSP instances.