Jan Węglarz

Scheduling Computer and Manufacturing Processes

No abstract

Project scheduling with finite or infinite number of activity processing modes - A survey

This paper surveys single-project, single-objective, deterministic project scheduling problems in which activities can be processed using a finite or infinite (and uncountable) number of modes concerning resources of various categories and types. The survey is based on a unified framework of a project scheduling model including resources, activities, objectives, and schedules. Most important models and solution approaches across the class of problems are characterized, and directions for future research are pointed out.

Simulated Annealing for Multi-Mode Resource-Constrained Project Scheduling

In this paper the resource-constrained project scheduling problem with multiple execution modes for each activity and the makespan as the minimization criterion is considered. A simulated annealing approach to solve this problem is presented. The feasible solution representation is based on a precedence feasible list of activities and a mode assignment. A comprehensive computational experiment is described, performed on a set of standard test problems constructed by the ProGen project generator. The results are analyzed and discussed and some final remarks are included.

Mathematical programming formulations for machine scheduling: a survey

Abstract Machine scheduling was and still is a rich and promising field for research with applications in manufacturing, logistics, computer architecture, communications, etc. Combinatorial complexity theory has now classified the great majority of known machine scheduling problems as ‘easy’ or ‘very hard’. However, in most cases, mathematical programming models have not accompanied the algorithmic developments for solving ‘easy’ scheduling problems, nor have they facilitates solutions for ‘hard’ problems. Nevertheless, the analysis of the mathematical programming models for some hard combinatorial problems together with their polyhedral properties has enabled important computational advances for such problems as the TSP. In order to assess the present status and the solution potential of mathematical programming formulations for machine scheduling, we have compiled a systematic, consistent survey of formulations. The discussion has been developed in tandem with the classification of a given problems complexity, since ‘solvability’ (i.e., the status of a problem as P or NP-hard) generally cannot be easily assessed from the formulation itself. A number of excellent survey papers on machine scheduling have appeared over the years (see the reference list), but none of them has been focused on mathematical formulations. This survey is the first one that attempts to compile a large number of mathematical programming formulations for scheduling into a single paper to ease the task of model building and testing scheduling formulations. Both, a newcomer and experienced researcher can use it as a reference point. Ultimately, mathematical programming formulations for scheduling problems might be used as a stepping stone to computational advances for some hard problems.

Computational experience with a backtracking algorithm for solving a general class of precedence and resource-constrained scheduling problems

In this paper computational results are presented with a very general, yet powerful backtracking procedure for solving the duration minimization and net present value maximization problems in a precedence and resource-constrained network. These networks are generally of the PERT/CPM variety, although it is not required that they be so. Among the advantages cited for our approach are low computer memory (storage) requirements and the ability to obtain improved solutions rapidly (heuristic properties). Since the resource-constrained project scheduling problem subsumes the job shop, flow shop, assembly line balancing, and related scheduling problems, our procedure can be used with little or no modification to solve a wide variety of problem types. Computational experience is reported for both mainframe and personal computer implementations.

DSS for multiobjective project scheduling

The paper presents a decision support system (DSS) for multiobjective project scheduling under multiple-category resource constraints. It handles quite a general class of nonpreemptive scheduling problems with renewable, nonrenewable and doubly-constrained resources, multiple performing modes of activities, precedence constraints in the form of an activity network and multiple project performance criteria of time and cost type. The DSS is based on three kinds of heuristics: parallel priority rules, simulated annealing and branch-and-bound. The last algorithm can even yield exact solutions when sufficient processing time is available. Some parts of the system are interactive, in particular, the search for the best compromise schedule. Graphical facilities enable a thorough evaluation of feasible schedules. Methodological foundations of the system and the algorithms used in the calculation phase are first explained. Then, a functional description of the system is made. The last part presents results of three test problems, in particular, an agricultural problem including 30 activities, multiple objectives and multiple-category resources.

Scheduling tasks and vehicles in a flexible manufacturing system

Due to their increasing applicability in modern industry, flexible manufacturing systems (FMSs), their design, and their control have been studied extensively in the recent literature. One of the most important issues that has arisen in this context is the FMS scheduling problem. This article is concerned with a new model of an FMS system, motivated by the practical application that takes into account both machine and vehicle scheduling. For the case of a given machine schedule, a simple polynomial-time algorithm is presented that checks the feasibility of a vehicle schedule and constructs it whenever one exists. Then a dynamic programming approach to construct optimal machine and vehicle schedules is proposed. This technique results in a pseudopolynomialtime algorithm for a fixed number of machines.

Tabu search for multi-mode resource-constrained project scheduling with schedule-dependent setup times

Abstract In this paper, a multi-mode resource-constrained project scheduling problem with schedule-dependent setup times is considered. A schedule-dependent setup time is defined as a setup time dependent on the assignment of resources to activities over time, when resources are, e.g., placed in different locations. In such a case, the time necessary to prepare the required resource for processing an activity depends not only on the sequence of activities but, more generally, on the locations in which successive activities are executed. Activities are non-preemptable, resources are renewable, and the objective is to minimize the project duration. A local search metaheuristic—tabu search is proposed to solve this strongly NP-hard problem, and it is compared with the multi-start iterative improvement method as well as with random sampling. A computational experiment is described, performed on a set of instances based on standard test problems constructed by the ProGen project generator. The algorithms are computationally compared, the results are analyzed and discussed, and some conclusions are given.

Perspectives in Modern Project Scheduling

Models.- A Practical and Accurate Alternative to PERT.- Proactive-Reactive Project Scheduling Trade-Offs and Procedures.- Resource Constrained Project Scheduling Models under Random Disturbances.- Due Dates and RCPSP.- RCPS with Variable Intensity Activities and Feeding Precedence Constraints.- Modelling Setup Times in Project Scheduling.- Algorithms.- Lower Bounds for Resource Constrained Project Scheduling Problem.- Justification Technique Generalizations.- A Metaheuristic Approach to the Resource Constrained Project Scheduling with Variable Activity Durations and Convex Cost Functions.- A Hybrid Genetic Algorithm Based on Intelligent Encoding for Project Scheduling.- Population Learning Algorithm for the Resource-Constrained Project Scheduling.- Resource Constrained Project Scheduling: a Hybrid Neural Approach.- Applications.- Selection and Scheduling of Pharmaceutical Research Projects.- Grid Multicriteria Job Scheduling with Resource Reservation and Prediction Mechanisms.- Resource-Constrained Project Scheduling with Time Windows.- CP-Based Decision Support for Project Driven Manufacturing.

On a methodology for discrete–continuous scheduling

Abstract Discrete–continuous problems of scheduling nonpreemptable jobs on parallel machines are considered. The problems arise e.g. when jobs are assigned to multiple parallel processors driven by a common electric, hydraulic or pneumatic power source. Existing models have assumed job processing rates as a function of the number of jobs currently being processed, or equivalently the number of machines currently in operation. In this paper a more general model is proposed in which processing rates of a job assigned to a machine depend on the amount of a continuous, i.e. continuously divisible resource (e.g. power) allotted to this job at a time. Thus the problem consists of two interrelated subproblems: (i) to sequence jobs on machines, and (ii) to allocate the continuous resource among jobs already sequenced. We provide a comprehensive analysis of the problem. This includes properties of optimal schedules, efficiently (in particular analytically) solvable cases, formulations of the possibly simplest mathematical programming problems for finding optimal schedules in the general case, heuristics and the worst-case analysis. Although our objective function in this paper is to minimize makespan of a set of independent jobs, the presented methodology can be applied to other criteria, precedence-related jobs, and many resource types (apart from, or instead of machines).