Kangbok Lee

Parallel machine scheduling under a grade of service provision

Abstract We consider the problem of scheduling parallel machines that process service requests from various customers who are entitled to many different grade of service (GoS) levels. We propose and analyze one simple way to ensure such differentiated service. In particular, we investigate how the longest processing time first algorithm (LPT) would perform in the worst case and show that a slight modification of LPT could significantly improve its worst-case performance.

Approximation algorithms for multi-agent scheduling to minimize total weighted completion time

We consider a multi-agent scheduling problem on a single machine in which each agent is responsible for his own set of jobs and wishes to minimize the total weighted completion time of his own set of jobs. It is known that the unweighted problem with two agents is NP-hard in the ordinary sense. For this case, we can reduce our problem to a Multi-Objective Shortest-Path (MOSP) problem and this reduction leads to several results including Fully Polynomial Time Approximation Schemes (FPTAS). We also provide an efficient approximation algorithm with a reasonably good worst-case ratio.

Online and semi-online scheduling of two machines under a grade of service provision

We consider the online scheduling of two machines under a grade of service (GoS) provision and its semi-online variant where the total processing time is known. Respectively for the online and semi-online problems, we develop algorithms with competitive ratios of 53 and 32 which are shown to be optimal.

Two-stage production scheduling with an outsourcing option

This paper considers a two-stage production scheduling problem in which each activity requires two operations to be processed in stages 1 and 2, respectively. There are two options for processing each operation: the first is to produce it by utilizing in-house resources, while the second is to outsource it to a subcontractor. For in-house operations, a schedule is constructed and its performance is measured by the makespan, that is, the latest completion time of operations processed in-house. Operations by subcontractors are instantaneous but require outsourcing cost. The objective is to minimize the weighted sum of the makespan and the total outsourcing cost. This paper analyzes how the models computational complexity changes according to unit outsourcing costs in both stages and describes the boundary between NP-hard and polynomially solvable cases. Finally, this paper presents an approximation algorithm for one NP-hard case.

The effect of machine availability on the worst-case performance of LPT

We consider the makespan minimization parallel machine scheduling problem where each machine may be unavailable for a known time interval. For this problem, we investigate how the worst-case behavior of the longest processing time first algorithm (LPT) is affected by the availability of machines. In particular, for given m machines, we analyze the cases where arbitrary number, λ, ranging from one to m - 1, machines are unavailable simultaneously. Then, we show that the makespan of the schedule generated by LPT is never more than the tight worst-case bound of 1 + ½ ⌊m/(m - λ)⌋ times the optimum makespan.

Scheduling jobs with equal processing times subject to machine eligibility constraints

We consider the problem of nonpreemptively scheduling a set of n jobs with equal processing times on m parallel machines so as to minimize the makespan. Each job has a prespecified set of machines on which it can be processed, called its eligible set. We consider the most general case of machine eligibility constraints as well as special cases of nested and inclusive eligible sets. Both online and offline models are considered. For offline problems we develop optimal algorithms that run in polynomial time, while for online problems we focus on the development of optimal algorithms of a new and more elaborate structure as well as approximation algorithms with good competitive ratios.

Complexity of single machine scheduling subject to nonnegative inventory constraints

This paper focuses on single machine scheduling subject to inventory constraints. Jobs either add items to an inventory or remove items from that inventory. Jobs that have to remove items cannot be processed if the required number of items is not available. We consider scheduling problems on a single machine with the minimization of the total weighted completion time, the maximum lateness, and the number of tardy jobs, respectively, as objective and determine their computational complexity. Since the general versions of our problems turn out to be strongly NP-hard, we consider special cases by assuming that different jobs have certain parameter values in common. We determine the computational complexity for all special cases when the objective is either to minimize total completion time or to minimize maximum lateness and for several special cases when the objective is either to minimize total weighted completion time or to minimize the number of tardy jobs.

Makespan minimization in online scheduling with machine eligibility

In this paper we provide a survey of online scheduling in parallel machine environments with machine eligibility constraints and the makespan as objective function. We first give a brief overview of the different parallel machine environments and then survey the various types of machine eligibility constraints, including tree-hierarchical processing sets, Grade of Service processing sets, interval processing sets, and nested processing sets. We furthermore describe the relationships between the various different types of processing sets. We proceed with describing two basic online scheduling paradigms, namely online over list and online over time. For each one of the two paradigms we survey all the results that have been recorded in the literature with regard to each type of machine eligibility constraints. We obtain also several extensions in various directions. In the concluding section we describe the most important open problems in this particular area.

Continuous slab caster scheduling and interval graphs

We define and solve a scheduling problem for operating the continuous steel slab caster which converts molten steel into slabs. The nature of our problem has an interesting connection to a special class of graphs known as interval graphs. We show that our problem can be seen as a variant of the clique partitioning problem defined on interval graphs and develop an optimal algorithm for it.

Operations scheduling with multiple resources and transportation considerations

We study a scheduling problem with the operations that require renewable as well as non-renewable resources. After an operation has been completed, the non-renewable resource is depleted whereas the renewable resource can be made available for the next operation. Of both the renewable and the non-renewable resources limited amounts are available and they need to be transported to the locations where they are needed. The operations have deadlines, and the availability of the renewable resources depends on the sequence of the operations. Such operations scheduling problems are commonly encountered in the practices of emergency logistics that deliver medical services to the affected areas after a disaster, where renewable resources typically refer to medical teams and non-renewable resources refer to medical supplies. We present a complexity classification for our problem and show where the borderline lies between NP-hardness and polynomial time solvability. We analyse the structural properties of our problem, provide strongly polynomial-time solutions for four special cases and list the cases that are computationally intractable. Finally, we propose a framework of heuristic procedures for solving more general versions of this problem.