An Exact Approach to Early/Tardy Scheduling with Release Dates

In this paper we consider the single machine earliness/tardiness scheduling problem with di?erent release dates and no unforced idle time. The problem is decomposed into a weighted earliness subproblem and a weighted tardiness subproblem. Lower bounding procedures are proposed for each of these subproblems, and the lower bound for the original problem is then simply the sum of the lower bounds for the two subproblems. The lower bounds and several versions of a branch-and-bound algorithm are then tested on a set of randomly generated problems, and instances with up to 30 jobs are solved to optimality. To the best of our knowledge, this is the first exact approach for the early/tardy scheduling problem with release dates and no unforced idle time.scheduling, early/tardy, release dates, lower bounds, branch-and-bound

Improved Lower Bounds for the Early/Tardy Scheduling Problem with No Idle Time

In this paper we consider the single machine earliness/tardiness scheduling problem with no idle time. Two of the lower bounds previously developed for this problem are based on lagrangean relaxation and the multiplier adjustment method, and require an initial sequence. We investigate the sensitivity of the lower bounds to the initial sequence, and experiment with di?erent dispatch rules and some dominance conditions. The computational results show that it is possible to obtain improved lower bounds by using a better initial sequence. The lower bounds are also incorporated in a branch-and-bound algorithm, and the computational tests show that one of the new lower bounds has the best performance for larger instances.scheduling, early/tardy, lower bound

Beam search heuristics for quadratic earliness and tardiness scheduling

In this paper, we present beam search heuristics for the single machine scheduling problem with quadratic earliness and tardiness costs, and no machine idle time. These heuristics include classic beam search procedures, as well as filtered and recovering algorithms. We consider three dispatching heuristics as evaluation functions, in order to analyse the effect of different rules on the performance of the beam search procedures. The computational results show that using better dispatching heuristics improves the effectiveness of the beam search algorithms. The performance of the several heuristics is similar for instances with low variability. For high variability instances, however, the detailed, filtered and recovering beam search procedures clearly outperform the best existing heuristic. The detailed beam search algorithm performs quite well, and is recommended for small to medium size instances. For larger instances, however, this procedure requires excessive computation times, and the recovering beam search algorithm then becomes the heuristic of choice.scheduling, heuristics, beam search, single machine, quadratic earliness, quadratic tardiness

Minimizing weighted total earliness, total tardiness and setup costs

The paper considers a (static) portfolio system that satisfies adding-up contraints and the gross substitution theorem. The paper shows the relationship of the two conditions to the weak dominant diagonal property of the matrix of interest rate elasticities. This enables to investigate the impact of simultaneous changes in interest rates on the asset demands.

Beam search heuristics for the single machine scheduling problem with linear earliness and quadratic tardiness costs

In this paper, we consider the single machine scheduling problem with linear earliness and quadratic tardiness costs, and no machine idle time. We present heuristic algorithms based on the beam search technique. These algorithms include classic beam search procedures, as well as the filtered and recovering variants. Several dispatching rules are considered as evaluation functions, in order to analyse the effect of different rules on the effectiveness of the beam search algorithms. The computational results show that using better rules indeed improves the performance of the beam search heuristics. The detailed, filtered and recovering beam search procedures outperform the best existing heuristic. The best results are given by the recovering and detailed variants, which provide objective function values that are quite close to the optimum. For small to medium size instances, either of these procedures can be used. For larger instances, however, the detailed beam search algorithm requires excessive computation times, and the recovering beam search procedure then becomes the heuristic of choice.scheduling, single machine, linear earliness, quadratic tardiness, beam search, heuristics

Permutation Flowshop Scheduling with Earliness and Tardiness Penalties

We address the permutation flowshop scheduling problem with earliness and tardiness penalties (E/T) and common due date of jobs. Large number of process and discrete parts industries follow flowshop type of production process. There are very few results reported for multi-machine E/T scheduling problems. We show that the problem can be sub-divided into three groups- one, where the due date is such that all jobs are necessarily tardy; the second, where the due date is such that it is not tight enough to act as a constraint on scheduling decision; and the third is a group of problems where the due date is in between the above two. We develop analytical results and heuristics for problems arising in each of these three classes. Computational results of the heuristics are reported. Most of the problems in this research are addressed for the first time in the literature. For problems with existing heuristics, the heuristic solution is found to perform better than the existing results.

Minimizing total inventory cost on a single machine in just-in-time manufacturing

The just-in-time concept decrees not to accept ordered goods before their due dates in order to avoid inventory cost. This bounces the inventory cost back to the manufacturer: products that are completed before their due dates have to be stored. Reducing this type of storage cost by preclusion of early completion conflicts with the traditional policy of keeping work-in-process inventories down. This paper addresses a single-machine scheduling problem with the objective of minimizing total inventory cost, comprising cost associated with work-in-process inventories and storage cost as a result of early completion. The cost components are measured by the sum of the job completion times and the sum of the job earlinesses. This problem differs from more traditional scheduling problems, since the insertion of machine idle time may reduce total cost. The search for an optimal schedule, however, can be limited to the set of job sequences, since for any sequence there is a clear-cut way to insert machine idle time in order to minimize total inventory cost. We apply branch-and-bound to identify an optimal schedule. We present five approaches for lower bound calculation, based upon relaxation of the objective function, of the state space, and upon Lagrangian relaxation. Key Words and Phrases: just-in-time manufacturing, inventory cost, work-in-process inventory, earliness, tardiness, machine idle time, branch-and-bound algorithm, Lagrangian relaxation

A Novel Approach to the Common Due-Date Problem on Single and Parallel Machines

This paper presents a novel idea for the general case of the Common Due-Date (CDD) scheduling problem. The problem is about scheduling a certain number of jobs on a single or parallel machines where all the jobs possess different processing times but a common due-date. The objective of the problem is to minimize the total penalty incurred due to earliness or tardiness of the job completions. This work presents exact polynomial algorithms for optimizing a given job sequence for single and identical parallel machines with the run-time complexities of $O(n \log n)$ for both cases, where $n$ is the number of jobs. Besides, we show that our approach for the parallel machine case is also suitable for non-identical parallel machines. We prove the optimality for the single machine case and the runtime complexities of both. Henceforth, we extend our approach to one particular dynamic case of the CDD and conclude the chapter with our results for the benchmark instances provided in the OR-library.Comment: Book Chapter 22 page