Minimizing Total Weighted Tardiness in Identical Parallel Machine with Sequence Dependent Setup Time Using Genetic Algorithm

This paper considers a scheduling problem in an identical parallel machine environment to minimize total weighted tardiness with the consideration of sequence dependent setup times. As the scheduling problem is proven to be NP-hard, a genetic algorithm is developed with the aim of providing good solution in a reasonable time to the scheduling problem. Computational experiments were performed to study the effectiveness of the genetic algorithm solution quality and the CPU time. Various dispatch heuristics were developed to provide initial solutions to the genetic algorithm besides comparing their solution quality with the genetic algorithm’s solution. The developed genetic algorithm has the capability to provide good results and good improvement compared to all the developed dispatching heuristics

Hybrid Tabu Search for batching and sequencing decisions on a single machine environment

The problem is represented mathematically as a new mixed integer linear programming (MILP) model. Extensive work has been carried out to investigate the capability of the MILP model in providing optimal solutions to small size problems which consist of 4 and 6 jobs per family with 2 and 3 families for a total of 640 problem instances. However, the MILP cannot produce optimal solutions for the problem of 8 jobs per family, 3 families and batch size 2. As the author recognises the limitations of the MILP model in solving large problems, the crucial need arises in finding other solution methods for the research problem

Integrated Approach For Production Planning And Sequencing Decisions In A Single Machine Batch Process

This thesis is motivated by a planning and scheduling decision problem encountered in a multi-product batch operations of a chemical firm in Malaysia. Batch processing means the processing of an integrated, non-divisible unit product such as volume of resin, polymer, or specialty chemical products. The objective of this research is to develop a practical solution approach for an industrial size problem that integrates production planning and sequencing decisions that involves multiple products, single machine in a multipurpose batch chemical manufacturing environment. Hence, a hierarchical framework which consists of three levels is developed which integrates the production planning and sequencing decisions which can answer to the management questions: "which product to make in which periodsand the exact production sequence that meet customer's due date?

An Integer Programming Model for a Nurse Scheduling Problem

This paper addresses a nurse scheduling problem that is present in a hospital. In order to accommodate the rising cost of sustaining and maintaining the hospital, there is a demand to analyse the manpower scheduling problem by not compromising the needs of the patients. Therefore, this study aims to apply a mathematical method to find the optimal number of nurses to be assigned for duties each day and shift in a hospital. An integer linear programming model is developed to represent the nurse scheduling problem. The mathematical model is solved by using the QM for windows software and the results provides an optimal solution to the nurse scheduling problem

A hybrid tabu search for batching and sequencing decisions in a single machine environment

This paper proposes a hybrid tabu search (HTS) to minimise the total weighted tardiness (TWT) for the batching and sequencing of jobs originating from incompatible families in which sequence dependent family setup times exist on single machine. The developed HTS includes distinguished features such as the strict arc based tabu classification along with dynamic tabu tenures, hybrid neighbourhood structures and iterative phases which consist of job and batch sequencing phases. The authors developed a testing methodology to determine the quality of the HTS solution. A mixed integer linear programing (MILP) model was developed to evaluate the optimality of the solution of the HTS for a small-size instance that consists of 640 problems. In addition, three dispatching rule heuristic combinations (EDD–EDD, EDD–BATCS and ATC–BATCS) were developed to test the HTS for large-size instances that deals with 1440 problems. The HTS provided comparable results with the MILP for small-size instances and outperformed the developed dispatching heuristics

Solving parallel machine scheduling problem with release dates using genetic algorithm

This research deals with a scheduling problem for parallel machines environment to minimize total weighted tardiness with the consideration of sequence dependent setup times and release dates. There are two research questions that need to be addressed: 1) How to allocate jobs on machines ? 2) How to sequence jobs on each machine? Therefore, this research aims to find an efficient solution method that answers the research questions with the goal of minimizing the total weighted tardiness with the presence of sequence dependent setup times. Due to the complexity of the problem at hand, the authors have developed genetic algorithm to find a solution to this problem. Furthermore, various dispatching rules were used to enhance the performance of the genetic algorithm in terms of the total weighted tardiness value

Minimizing Makespan with Release Dates in a Single Machine Scheduling Problem By Using Tabu Search

This paper considers a single machine scheduling problem of minimizing makespan (Cmax) which takes into consideration of real life aspects that includes release dates and sequence dependent setup times for industrial size problem. The problem is proven to be NP-hard and therefore the only solution available in the literature is by constructing heuristics. A metaheuristic which is Tabu search was developed for solving the problem in this paper. Besides that, three initial solutions for the Tabu search based on dispatching rules have been developed. Each of these dispatching heuristics serves as an initial solution to the Tabu search besides playing a role in testing the efficiency of the final results of the Tabu search. Based on the experiments conducted, tabu search was able to provide an improvement compared to the initial solution in terms of the objective function although the magnitude of improvement was small

Scheduling Incompatible Job Families on A Single Machine: A Two-Level Heuristic Approach

We introduce a two-level heuristic approach for solving jobs originated from incompatible job families that aims to minimize the total weighted tardiness. At the first level, an apparent tardiness cost with setups (ATCS) for a single machine is developed. The second level, a Tabu Search (TS) heuristic is developed that uses the initial solution obtained by the ATCS and provides a better solution if it exist. Real industrial data is used to test and validate the proposed methodology. The results indicate that the suggested approach can provide solution in a reasonable good time that can be of use for the decision maker