Natalia V. Shakhlevich

NP-hardness of shop-scheduling problems with three jobs

This paper deals with the problem of scheduling n jobs on m machines in order to minimize the maximum completion time or mean flow time of jobs. We extend the results obtained in Sotskov (1989, 1990, 1991) on the complexity of shop-scheduling problems with n = 3. The main result of this paper is an NP-hardness proof for scheduling 3 jobs on 3 machines, whether preemptions of operations are allowed or forbidden.

Complexity of mixed shop scheduling problems: A survey

We survey recent results on the computational complexity of mixed shop scheduling problems. In a mixed shop, some jobs have fixed machine orders (as in the job shop), while the operations of the other jobs may be processed in arbitrary order (as in the open shop). The main attention is devoted to establishing the boundary between polynomially solvable and NP-hard problems. When the number of operations per job is unlimited, we focus on problems with a fixed number of jobs.

Minimizing total weighted completion time in a proportionate flow shop

We study the special case of the m machine flow shop problem in which the processing time of each operation of job j is equal to pj; this variant of the flow shop problem is known as the proportionate flow shop problem. We show that for any number of machines and for any regular performance criterion we can restrict our search for an optimal schedule to permutation schedules. Moreover, we show that the problem of minimizing total weighted completion time is solvable in O(n2) time.

Complexity Results for Flow-Shop and Open-Shop Scheduling Problems with Transportation Delays

We consider shop problems with transportation delays where not only the jobs on the machines have to be scheduled, but also transportation of the jobs between the machines has to be taken into account. Jobs consisting of a given number of operations have to be processed on machines in such a way that each machine processes at most one operation at a time and a job is not processed by more than one machine simultaneously. Transportation delays occur if a job changes from one machine to another. The objective is to find a feasible schedule which minimizes some objective function. A survey of known complexity results for flow-shop and open-shop environments is given and some new complexity results are derived.

Single machine scheduling with controllable release and processing parameters

This paper considers single machine scheduling problems in which the job processing times and/or their release dates are controllable. Possible changes to the controllable parameters are either individual or done by controlling the relevant processing or release rate. The objective is to minimize the sum of the makespan plus the cost for changing the parameters. For the problems of this type, we provide a number of polynomial-time algorithms and give a fairly complete complexity classification.

Pre-Emptive Scheduling Problems with Controllable Processing Times

We consider a range of single machine and identical parallel machine pre-emptive scheduling models with controllable processing times. For each model we study a single criterion problem to minimize the compression cost of the processing times subject to the constraint that all due dates should be met. We demonstrate that each single criterion problem can be formulated in terms of minimizing a linear function over a polymatroid, and this justifies the greedy approach to its solution. A unified technique allows us to develop fast algorithms for solving both single criterion problems and bicriteria counterparts.

Scheduling with controllable release dates and processing times: Total completion time minimization

Abstract The single machine scheduling problem with two types of controllable parameters, job processing times and release dates, is studied. It is assumed that the cost of compressing processing times and release dates from their initial values is a linear function of the compression amounts. The objective is to minimize the sum of the total completion time of the jobs and the total compression cost. For the problem with equal release date compression costs we construct a reduction to the assignment problem. We demonstrate that if in addition the jobs have equal processing time compression costs, then it can be solved in O(n2) time. The solution algorithm can be considered as a generalization of the algorithm that minimizes the makespan and total compression cost. The generalized version of the algorithm is also applicable to the problem with parallel machines and to a range of due-date scheduling problems with controllable processing times.

Tabu search and lower bounds for a combined production-transportation problem

In this paper we consider a combined production-transportation problem, where n jobs have to be processed on a single machine at a production site before they are delivered to a customer. At the production stage, for each job a release date is given; at the transportation stage, job delivery should be completed not later than a given due date. The transportation is done by m identical vehicles with limited capacity. It takes a constant time to deliver a batch of jobs to the customer. The objective is to find a feasible schedule minimizing the maximum lateness. After formulating the considered problem as a mixed integer linear program, we propose different methods to calculate lower bounds. Then we describe a tabu search algorithm which enumerates promising partial solutions for the production stage. Each partial solution is complemented with an optimal transportation schedule (calculated in polynomial time) achieving a coordinated solution to the combined production-transportation problem. Finally, we present results of computational experiments on randomly generated data.

Scheduling with controllable release dates and processing times: Makespan minimization

Abstract The paper deals with the single-machine scheduling problem in which job processing times as well as release dates are controllable parameters and they may vary within given intervals. While all release dates have the same boundary values, the processing time intervals are arbitrary. It is assumed that the cost of compressing processing times and release dates from their initial values is a linear function of the compression amount. The objective is to minimize the makespan together with the total compression cost. We construct a reduction to the assignment problem for the case of equal release date compression costs and develop an O( n 2 ) algorithm for the case of equal release date compression costs and equal processing time compression costs. For the bicriteria version of the latter problem with agreeable processing times, we suggest an O( n 2 ) algorithm that constructs the breakpoints of the efficient frontier.

Parallel batch scheduling of equal-length jobs with release and due dates

In this paper we study parallel batch scheduling problems with bounded batch capacity and equal-length jobs in a single and parallel machine environment. It is shown that the feasibility problem 1|p-batch,b<n,rj,pj=p,Cj≤dj|− can be solved in O(n2) time and that the problem of minimizing the maximum lateness can be solved in O(n2log n) time. For the parallel machine problem P|p-batch,b<n,rj,pj=p,Cj≤dj|− an O(n3log n)-time algorithm is provided, which can also be used to solve the problem of minimizing the maximum lateness in O(n3log 2n) time.