This thesis is divided into two parts. The first part of the thesis deals with the study of heuristic based approaches for approximating Pareto fronts. We propose a new Double Archive Pareto local search algorithm for solving multi-objective combinatorial optimization problems. We embed our technique into a genetic framework where our algorithm restarts with the set of new solutions formed by t...

in this paper, the use of weighted pairwise likelihood instead of the full likelihood in estimating the parameters of the multivariate ar(1) is investigated. a closed formula for typical elements of the godambe information(sandwich information) is presented. some efficiency calculations are also given to discuss the feasibility andcomputational advantages of the weighted pairwise likelihood app...

Supply chain scheduling is a new emerging area of research. We study batch arrival scheduling problems at the manufacturer in a multi-level customer-centric supply chain, where promised job due dates are considered constraints which must be satisfied. We analyze the tradeoff between inventory holding costs and batch delivery costs. We show that the problems are closely related to batch scheduli...

Abstract: This paper considers a bi-criteria scheduling on parallel machines in fuzzy environment which optimizes the weighted flow time and maximum tardiness. The fuzziness, vagueness or uncertainty in processing time of jobs is represented by triangular fuzzy membership function. The bi-criteria problem with weighted flow time and maximum tardiness as primary and secondary criteria, respectiv...