Minimizing total weighted completion time in a two-machine flow shop scheduling under simple linear deterioration

In this paper, we address a two-machine flow shop scheduling problem under simple linear deterioration. By a simple linear deterioration function, we mean that the processing time of a job is a simple linear function of its execution start time. The objective is to find a sequence that minimizes total weighted completion time. Optimal schedules are obtained for some special cases. For the general case, several dominance properties and two lower bounds are derived to speed up the elimination process of a branch-and-bound algorithm. A heuristic algorithm is also proposed to overcome the inefficiency of the branch-and-bound algorithm. Computational analysis on randomly generated problems is conducted to evaluate the branch-and-bound algorithm and heuristic algorithm.     

Two simple constant ratio approximation algorithms for minimizing the total weighted completion time on a single machine with a fixed non-availability interval

In this note, we consider the scheduling problem of minimizing the sum of the weighted completion times on a single machine with one non-availability interval on the machine under the non-resumable scenario. Together with a recent 2-approximation algorithm designed by Kacem [I. Kacem, Approximation algorithm for the weighted flow-time minimization on a single machine with a fixed non-availability interval, Computers & Industrial Engineering 54 (2008) 401–410], this paper is the first successful attempt to develop a constant ratio approximation algorithm for this problem. We present two approaches to designing such an algorithm. Our best algorithm guarantees a worst-case performance ratio of 2+ε$2+\epsilon$.     

Two-machine flow-shop scheduling with equal processing time on the second machine for minimizing total weighted completion time

We consider the classical two-machine flow-shop scheduling for minimizing the total weighted completion time. For this problem, the computational complexity of a version in which the jobs have a common processing time on the second machine, has not been addressed. We show that the problem is unary NP-hard, answering an open problem posed in Zhu et al. (2016). Then we present an approximation algorithm for the problem with worst-case performance ratio at most 2.     

NP-hardness of the single-variable-resource scheduling problem to minimize the total weighted completion time

Baker and Nuttle [K.R. Baker, H.L.W. Nuttle, Sequencing independent jobs with a single resource, Naval Research Logistics Quarterly 27 (1980) 499–510] studied the following single-variable-resource scheduling problem: sequencing n jobs for processing by a single resource to minimize a function of job completion times, when the availability of the resource varies over time. When the objective function to be minimized is the total weighted completion time, Baker and Nuttle conjectured that the problem is NP-hard. We show in this note that the conjecture is true.     

A tabu search algorithm for the single machine total weighted tardiness problem

In this study, a tabu search (TS) approach to the single machine total weighted tardiness problem (SMTWT) is presented. The problem consists of a set of independent jobs with distinct processing times, weights and due dates to be scheduled on a single machine to minimize total weighted tardiness. The theoretical foundation of single machine scheduling with due date related objectives reveal that the problem is NP-hard, rendering it a challenging area for meta-heuristic approaches. This paper presents a totally deterministic TS algorithm with a hybrid neighborhood and dynamic tenure structure, and investigates the strength of several candidate list strategies based on problem specific characteristics in increasing the efficiency of the search. The proposed TS approach yields very high quality results for a set of benchmark problems obtained from the literature.     

A lower bound for weighted completion time variance

We consider a single machine scheduling problem to minimize the weighted completion time variance. This problem is known to be NP-hard. We propose a heuristic and a lower bound based on job splitting and the Viswanathkumar and Srinivasan procedure. The test on more than 2000 instances shows that this lower bound is very tight and the heuristic yields solutions very close to optimal ones since the gap between the solution given by the heuristic and the lower bound is very small.     

Unrelated parallel-machine scheduling with deterioration effects and deteriorating multi-maintenance activities for minimizing the total completion time

This paper investigates scheduling problems with simultaneous considerations of deterioration effects and deteriorating multi-maintenance activities on unrelated parallel machines. We examine two models of scheduling with the deterioration effect, namely the job-dependent and position-dependent deterioration model and the time-dependent deterioration model. We assume that each machine may be subject to several maintenance activities over the scheduling horizon, and the duration of maintenance on a machine depends on its running time. Moreover, due to the restriction of the budget of maintenance, the upper bound of the total maintenance frequencies on all the machines is assumed to be known in advance. The objective is to find jointly the optimal maintenance frequencies, the optimal maintenance positions, and the optimal job sequences such that the total completion time is minimized. If the number of machines is fixed, we introduce polynomial time solutions for all the versions of the problem under study.     

Pareto optima for total weighted completion time and maximum lateness on a single machine

We consider the single-machine bicriterion scheduling problem of enumerating the Pareto-optimal sequences with respect to the total weighted completion time and the maximum lateness objectives. We show that the master sequence concept originally introduced for 1|r_j|∑w_jU_j by Dauzère-Pérès and Sevaux is also applicable to our problem and a large number of other sequencing problems. Our unified development is based on exploiting common order-theoretic structures present in all these problems. We also show that the master sequence implies the existence of global dominance orders for these scheduling problems. These dominance results were incorporated into a new branch and bound algorithm, which was able to enumerate all the Pareto optima for over 90% of the 1440 randomly generated problems with up to n=50 jobs. The identification of each Pareto optimum implicitly requires the optimal solution of a strongly NP-hard problem. The instances solved had hundreds of these Pareto solutions and to the best of our knowledge, this is the first algorithm capable of completely enumerating all Pareto sequences within reasonable time and space for a scheduling problem with such a large number of Pareto optima.     

Approximating total weighted completion time on identical parallel machines with precedence constraints and release dates

We present a $(2+2ln2+\epsilon )$-approximation algorithm for the classical nonpreemptive scheduling problem to minimize the total weighted completion time of jobs on identical parallel machines subject to release dates and precedence constraints, improving upon the previously best known 4-approximation algorithm from 1998. The result carries over to the more general problem with precedence delays and generalizes a recent result by Li (2017) for the problem without release dates or delays.     

Non-identical parallel-machine scheduling research with minimizing total weighted completion times: Models,relaxations and algorithms

We consider a class of non-identical parallel-machine scheduling problems in which the goal is to minimize total (or mean) weighted (or unweighted) completion time. Models and relaxations are collected and classified in this paper. Heuristics and optimizing techniques are surveyed for the problems. And a few of interesting areas for future research are also provided.     

Reducibility among single machine weighted completion time scheduling problems

Various sum of weighted completion time problems are compared. The constraints considered include release date, deadline, and continuous machine processing. Relations between the problems are developed by examining the computational complexity of transforming one problem class into another. These results give indications of the relative computational effort required to solve different problem classes.     

Two-agent single-machine scheduling problems under increasing linear deterioration

A new scheduling model in which both two-agent and increasing linear deterioration exist simultaneously is investigated in this paper. The processing time of a job is defined as an increasing linear function of its starting time. Two agents compete to perform their respective jobs on a common single machine and each agent has his own criterion to optimize. We introduce an increasing linear deterioration model into the two-agent single-machine scheduling, where the goal is to minimize the objective function of the first agent with the restriction that the objective function of the second agent cannot exceed a given upper bound. We study two scheduling problems with the different combinations of two agents’ objective functions: makespan, maximum lateness, maximum cost and total completion time. We propose the optimal properties and present the optimal polynomial time algorithms to solve the scheduling problems, respectively.     

Approximability of single machine scheduling with fixed jobs to minimize total completion time

We consider the single machine scheduling problem to minimize total completion time with fixed jobs, precedence constraints and release dates. There are some jobs that are already fixed in the schedule. The remaining jobs are free to be assigned to any free-time intervals on the machine in such a way that they do not overlap with the fixed jobs. Each free job has a release date, and the order of processing the free jobs is restricted by the given precedence constraints. The objective is to minimize the total completion time. This problem is strongly NP-hard. Approximability of this problem is studied in this paper. When the jobs are processed without preemption, we show that the problem has a linear-time n-approximation algorithm, but no pseudopolynomial-time (1 − δ)n-approximation algorithm exists even if all the release dates are zero, for any constant δ > 0, if P ≠ NP, where n is the number of jobs; for the case that the jobs have no precedence constraints and no release dates, we show that the problem has no pseudopolynomial-time (2 − δ)-approximation algorithm, for any constant δ > 0, if P ≠ NP, and for the weighted version, we show that the problem has no polynomial-time 2^q(n)-approximation algorithm and no pseudopolynomial-time q(n)-approximation algorithm, where q(n) is any given polynomial of n. When preemption is allowed, we show that the problem with independent jobs can be solved in O(n log n) time with distinct release dates, but the weighted version is strongly NP-hard even with no release dates; the problems with weighted independent jobs or with jobs under precedence constraints are shown having polynomial-time n-approximation algorithms. We also establish the relationship of the approximability between the fixed job scheduling problem and the bin-packing problem.     

Scheduling orders on either dedicated or flexible machines in parallel to minimize total weighted completion time

We are interested in the problem of scheduling orders for different product types in a facility with a number of machines in parallel. Each order asks for certain amounts of various different product types which can be produced concurrently. Each product type can be produced on a subset of the machines. Two extreme cases of machine environments are of interest. In the first case, each product type can be produced on one and only one machine which is dedicated to that product type. In the second case, all machines are identical and flexible; each product type can be produced by any one of the machines. Moreover, when a machine in this case switches over from one product type to another, no setup is required. Each order has a release date and a weight. Preemptions are not allowed. The objective is minimizing the total weighted completion time of the orders. Even when all orders are available at time 0, both types of machine environments have been shown to be NP-hard for any fixed number (≥2) of machines. This paper focuses on the design and analysis of approximation algorithms for these two machine environments. We also present empirical comparisons of the various algorithms. The conclusions from the empirical analyses provide insights into the trade-offs with regard to solution quality, speed, and memory space. Electronic Supplementary Material The online version of this article () contains supplementary material, which is available to authorized users. This research is supported by the National Science Foundation through grants DMI-0300156 and DMI-0245603.     

An improved branch and bound algorithm for single machine scheduling with deadlines to minimize total weighted completion time

We consider a scheduling problem in which n jobs with distinct deadlines are to be scheduled on a single machine. The objective is to find a feasible job sequence that minimizes the total weighted completion time. We present an efficient branch-and-bound algorithm that fully exploits the principle of optimality. Favorable numerical results are also reported on an extensive set of problem instances of 20-120 jobs.     

A branch-and-check algorithm for minimizing the weighted number of late jobs on a single machine with release dates

In this paper we consider the scheduling problem of minimizing the weighted number of late jobs on a single machine (1|_rj|∑_wjUj)$\left(1|r_j|\sum w_j{U}_j\right)$. A branch-and-check algorithm is proposed, where a relaxed integer programming formulation is solved by branch-and-bound and infeasible solutions are cut off using infeasibility cuts. We suggest two ways to generate cuts. First, tightened “no-good” cuts are derived using a modification of the algorithm by Carlier (1982, EJOR, v.11, 42–47) which was developed for the problem of minimizing maximum lateness on a single machine. Secondly we show how to create cuts by using constraint propagation. The proposed algorithm is implemented in the Mosel modelling and optimization language. Computational experiments on instances with up to 140 jobs are reported. A comparison is presented with the exact approach of Péridy at al. (2003, EJOR, v.148, 591–603).