Anand S. Kunnathur

Minimizing the makespan with late start penalties added to processing times in a single facility scheduling problem

Abstract This paper considers the following scheduling problem: Minimize the makespan in a single facility problem where the processing time of a job consists of a fixed and a variable part. The variable part depends on the start time of the job. The objective is to minimize makespan. Two optimizing algorithms based on dynamic programming and branch-and-bound techniques and five heuristic rules have been proposed. The heuristic solutions have been compared with the optimal solution for upto 7 jobs to identify the best heuristic. The detailed computational results for the branch-and-bound and the best heuristic rule are then obtained for problems with up to 15 jobs.

IS outsourcing management competence dimensions: instrument development and relationship exploration

In this paper, we discuss our investigation of IS outsourcing management competences, their relationships and measurement. First, three theoretical perspectives were applied to explain the nature of the IS outsourcing phenomenon. Second, IS outsourcing management competence dimensions and their measures were generated, based on the literature. Third, data was then gathered to refine measures empirically and test proposed competences and their relationships. The theoretical development and empirical testing filled the gap in IS outsourcing management competence research resulting in important implications for IS outsourcing practitioners.

Single machine scheduling with start time dependent processing times: Some solvable cases

Abstract In this paper a new type of single machine scheduling problem, in which the processing time is a binary function of a common start time due date is defined. The jobs have processing time penalties for starting after the due date, and the objective is to minimize the sum of the weighted completion times. The general case addressed here is for jobs with common pre-duedate processing time, general post-duedate processing time penalties, and general weights. A switching algorithm is proposed for this case and we conjecture that it is optimal. A 0–1 quadratic programming formulation of this problem is presented. Solvable cases, one with two different weights, another with two different penalties and another with structured weights and penalties have been identified and polynomial time optimal algorithms have been proposed for them.

Optimal repayment policies for multiple loans

This paper extends the applications of scheduling theory to certain problems in the area of finance. Specifically, a branch and bound algorithm to identify optimal repayment policies for multiple loans (credit purchases) has been developed. Each loan qualifies for a discount if it is paid on or before a certain date and a penalty is imposed if it is paid after its due date. These two dates are different in general. It is assumed that the cash for repayment is generated at a constant rate per day and it can be invested so that it continues to earn money until used for repayment. The objective is to minimize the present value of all future cash outflows.

Expert systems adoption: an analytical study of managerial issues and concerns

Abstract The experience of introducing expert systems technology into six automotive component manufacturing organizations in the mid-western United States is described. The domain of expert system application as well as the procedural and organizational hurdles that were encountered are also documented. An overview of relevant literature shows the shortage of studies of this kind. A synthesis is provided of the study observations and implications for better management of expert systems adoption in manufacturing.

Dynamic rescheduling using a simulation‐based expert system

The development of a rule‐based expert system (ES), driven by a discrete event simulation model, that performs dynamic shop scheduling is described. Based on a flowtime prediction heuristic that has been developed and base‐line runs to establish the efficacy of scheduling strategies such as shortest processing time (SPT), critical ratio, total work, etc., a rescheduling‐based dispatching strategy is investigated in a dynamic job shop environment. The results are discussed and analyzed.

Dynamic rescheduling of a job shop: a simulation study

The development of a rule based Expert System (ES), driven by a discrete event simulation model, that performs dynamic shop scheduling is described. Based on a flowtime prediction heuristic that we have developed and base-line runs to establish the efficacy of scheduling strategies such as SPT, Critical Ratio, Total Work etc, a re-scheduling based dispatching strategy is investigated in a dynamic job shop environment. The results are discussed and analyzed.

Shipment partitioning and routing to minimize makespan in a transportation network

This paper addresses the problem of partitioning and transporting a shipment of known size through an n-node public transportation network with known scheduled departure and arrival times and expected available capacities for each departure. The objective is to minimize the makespan of shipping. The problem while practical in its scope, has received very little attention in the literature perhaps because of the concentration of research in vehicle routing without regard to partitioning and partitioning without regard to routing. A general non-linear programming model is developed. The model is then converted into a linear model through the Routing First and Assignment Second approach. This approach is different from the general decomposition approaches since they normally do not guarantee optimality. However, the linear model still involves a large number of constraints, and solution is not attempted here. Instead, three heuristics are proposed for solving the problem. Two of the heuristics use iterative techniques to evaluate all possible paths. The third heuristic uses a max-flows approach based upon aggregated capacities to reduce the size of the network presented to the other heuristics. This allows for a good starting point for other heuristics, and may impact the total computational effort. We find that the heuristics developed perform well because in the case of networks that are not congested, they find the optimal solution.

Adoption of modern technology in small manufacturing firms: a study of issues and concerns

The manufacturing sector in general, and small manufacturers in particular, are faced with fierce national, regional and global competition. Trade alliances, such as NAFTA, which have been entered into by the USA will add to this competitive burden. Modernisation of manufacturing facilities through the infusion of computerised manufacturing and information processing technology has become imperative in this environment. A body of research is only now beginning to be developed for the identification of the issues and considerations that impede or facilitate modernisation of small manufacturing. This research is an attempt to contribute towards filling the gap in understanding of small manufacturing issues and concerns.

Multiple copy file allocation and placement in a distributed information network

Abstract The problem of minimizing query, update and storage costs in a distributed information network in which one or more m sites may receive a copy of one or more of m different files is studied in this work. The problem is known to be NP complete. Cost efficiency considerations further dictate that for each query emanating site there be exactly one designated responder site. A model to solve the problem is formulated. Two heuristics based on the problem structure are proposed and their performance relative to each other and to an optimal procedure is reported for problems with up to four files and up to eight sites.