Project sequencing problem for capacity expansion

Abstract

In this thesis, we examine the project sequencing problem for capacity expansion, where a project can be implemented only at discrete time points and distribution costs as well as expansion costs are considered. The objective of this problem is to find the sequence of expansions necessary to provide sufficient capacities to meet the regional demands in all periods at a minimum total cost which is the sum of capacity expansion costs and distribution costs. Project sequencing problems are difficult combinatorial problems for which the optimal solutions can be found only if the number of possible projects is small. Dynamic programming algorithm can not be applied if the number of projects is large. Here we concentrate on solving large size problems efficiently. Assuming independence of each project, this problem can be formulated as a mixed integer programming problem, and is solved using Lagrangean relaxation method combined with subgradient optimization procedure. Several heuristics to find a feasible solution are presented. Finally, camputational results are provided and future research directions are discussed.