A multiple criteria decision making approach for the assembly line balancing problem

Abstract

In practice, measuring total profit for a given assembly line balancing (ALB) problem is an involved process that is sometimes impossible because of much uncertainty and unavailability of data. In this paper, ALB is formulated as a multiple criteria problem where several easily quantifiable criteria (objectives) and constraints are defined. Objective functions include number of stations, cycle time, and operations cost, all to be minimized. After a discussion of applications and an overview of multiple criteria decision making (MCDM) approaches for ALB, the MCDM-ALB problem is formulated. Basic definitions and properties of MCDM for ALB are outlined and then an interactive MCDM approach is developed for solving the MCDM-ALB problem. To solve the problem, the decision maker (DM) interactively responds to paired comparisons of multicriteria alternatives. Through a limited number of interactions with the DM, the most preferred alternative is obtained. Many unexplored alternatives are eliminated by using a one-dimensional multiple criteria search. To present the DM's preference, we use the most flexible and general class of utility functions; namely, either quasi-concave or quasi-convex utility functions. An example is solved and computational experiments are reported. It is demonstrated that the bicriteria ALB, cycle time versus number of stations, can be easily solved by using the developed procedure. For the case that there are different criteria, an improved goal programming is developed to solve the MCDM-ALB problem. The motivation for development of the method, based on a case study of a lamp-making plant of the General Electric Company, is discussed.