An interactive approach to multicriteria sorting for quasiconcave value functions

In this article, we develop an interactive algorithm to place alternatives in ordered preference classes for a decision maker (DM) with an increasing quasiconcave value function. Such value functions are quite general in that they include linear and concave value functions. Our aim is to elicit sorting information from the DM as few times as possible; our algorithm places other alternatives using previous responses from the DM utilizing properties of quasiconcave value functions. As an application, we sort 81 global MBA programs into preference classes using criteria such as alumni career progress, idea generation, and diversity. We study the performance of our proposed algorithm, when we change the number of criteria, number of alternatives, and introduce response errors. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 447–457, 2014     

A heuristic approach to bicriteria scheduling

We consider the problem of sequencing jobs on a single machine while minimizing a nondecreasing function of two criteria. We develop a heuristic procedure that quickly finds a good solution for bicriteria scheduling. The procedure is based on using several arcs in the criterion space that are representative of the possible locations of nondominated solutions. By sampling a small number of points on these arcs, a promising point is identified in the criterion space for each arc. An efficient sequence in the neighborhood of each of the promising points is found and the best of these efficient sequences is selected as the heuristic solution. We implement the procedure for two different bicriteria scheduling problems: (i) minimizing total flowtime and maximum tardiness and (ii) minimizing total flowtime and maximum earliness. The computational experience on a wide variety of problem instances show that the heuristic approach is very robust and yields good solutions. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 777–789, 1999     

Note: Bicriteria scheduling for minimizing flow time and maximum tardiness

We consider the bicriteria problem of minimizing total flow time and maximum tardiness penalties for a given set of jobs on a single machine. We develop an algorithm that finds the optimal schedule for any given monotonic function of the two criteria by generating only a small subset of the efficient schedules.     

Scheduling with tool changes to minimize total completion time: A study of heuristics and their performance

The machine scheduling literature does not consider the issue of tool change. The parallel literature on tool management addresses this issue but assumes that the change is due only to part mix. In practice, however, a tool change is caused most frequently by tool wear. That is why we consider here the problem of scheduling a set of jobs on a single CNC machine where the cutting tool is subject to wear; our objective is to minimize the total completion time. We first describe the problem and discuss its peculiarities. After briefly reviewing available theoretical results, we then go on to provide a mixed 0–1 linear programming model for the exact solution of the problem; this is useful in solving problem instances with up to 20 jobs and has been used in our computational study. As our main contribution, we next propose a number of heuristic algorithms based on simple dispatch rules and generic search. We then discuss the results of a computational study where the performance of the various heuristics is tested; we note that the well‐known SPT rule remains good when the tool change time is small but deteriorates as this time increases and further that the proposed algorithms promise significant improvement over the SPT rule. © 2002 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

Constructing a strict total order for alternatives characterized by multiple criteria: An extension

The problem of finding a strict total order for a finite set of multiple criteria alternatives is considered. Our research extends previous work by us, which considered finding a partial order for a finite set of alternatives. We merge the preference information extracted from the preference cones and corresponding polyhedral sets, with the information derived from pairwise comparisons of two alternatives, yielding a preference matrix. This preference matrix is used as input to an integer programming model to obtain a strict total order that provides a transitive ranking for the set of alternatives. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 155–163, 2014     

An EOQ model with multiple suppliers and random capacity

We consider an EOQ model with multiple suppliers that have random capacities, which leads to uncertain yield in orders. A given order is fully received from a supplier if the order quantity is less than the supplier's capacity; otherwise, the quantity received is equal to the available capacity. The optimal order quantities for the suppliers can be obtained as the unique solution of an implicit set of equations in which the expected unsatisfied order is the same for each supplier. Further characterizations and properties are obtained for the uniform and exponential capacity cases with discussions on the issues related to diversification among suppliers. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

An interactive procedure for selecting acceptable alternatives in the presence of multiple criteria

In this paper, we consider the multiple criteria decision‐making problem of partitioning alternatives into acceptable and unacceptable sets. We develop interactive procedures for the cases when the underlying utility function of the decision maker is linear, quasiconcave, and general monotone. We present an application of the procedures to the problem of admitting students to the master's degree program at the Industrial Engineering Department, Middle East Technical University. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 592–606, 2001.     

Heuristic procedure for a multiproduct dynamic lot-sizing problem with coordinated replenishments

In this article we develop a heuristic procedure for a multiproduct dynamic lot-sizing problem. In this problem a joint setup cost is incurred when at least one product is ordered in a period. In addition to the joint setup cost a separate setup cost for each product ordered is also incurred. The objective is to determine the product lot sizes, over a finite planning horizon, that will minimize the total relevant cost such that the demand in each period for each product is satisfied without backlogging. In this article we present an effective heuristic procedure for this problem. Computational results for the heuristic procedure are also reported. Our computational experience leads us to conclude that the heuristic procedure may be of considerable value as a decision-making aid to production planners in a real-world setting. © 1994 John Wiley & Sons, Inc.