Calendar Constraints Research Articles

Mixed-Integer Linear Programming, Constraint Programming and a Novel Dedicated Heuristic for Production Scheduling in a Packaging Plant

In this paper, we are discussing a research project aiming to optimize the scheduling of production orders within a real application in the packaging field. As a first approach, we model the problem as an extended version of the hybrid and flexible flowshop scheduling problem with precedence constraints, parallel machines, and sequence-dependent setups. The optimization objective considered is the minimization of the total tardiness. To tackle this problem, we use two methodologies: mixed-integer linear programming (MILP) and constraint programming (CP). These two models were further extended by adding resource calendar constraints named also availability constraints; this implies that the tasks should be scheduled only when the machine is available. The different proposed models were compared to each other on a set of generated benchmarks that reflect the specific properties of the industrial partner. Finally, as the studied configuration relies on practical real-world application, where thousands of orders are produced monthly, a novel dedicated heuristic was designed to address the need for quick solutions. The latter outperforms the other proposed algorithms for expected total tardiness minimization. The proposed problem can be readily modified to suit a wide range of real-world situations involving the scheduling of activities that share similar characteristics.

A column generation-based diving heuristic to solve the multi-project personnel staffing problem with calendar constraints and resource sharing

Project managers are often responsible for the management of multiple projects and associated personnel budgeting decisions. In order to determine the workforce size and mix accurately, we integrate the multi-project scheduling problem and personnel staffing problem. We construct a baseline personnel roster that takes the personnel scheduling constraints into account and model the workload stemming from the project activities as an endogenous variable in the model. In order to decrease the overall staffing budget, we consider the sharing of resources, i.e. personnel resources can be transferred between projects. In the problem under study, we consider unproductive resource transfer times and different restrictions related to the sharing of resources imposed on the schedule of individual workers, which is often neglected in the literature. We propose a multi-stage solution procedure that exploits the optimal linear programming solution, obtained via column generation, to find a high-quality integer solution based on a diving heuristic. In order to improve the computational performance, different speed-up mechanisms are included relying on a state space reduction. Detailed computational experiments are presented to evaluate and benchmark different alternative optimisation strategies. Managerial insights are provided which give insight in the benefits of resource sharing.

A two-stage ant colony algorithm for hybrid flow shop scheduling with lot sizing and calendar constraints in printed circuit board assembly

This paper investigates a multi-stage hybrid flow shop scheduling problem with challenging characteristics including lot sizing, calendar constraints and sequence-dependent setup times in a real-world printed circuit board (PCB) assembly shop. Besides, other characteristics such as unrelated parallel machines and stage skipping also complicate the problem. Such features make the scheduling problem very difficult to find an optimal or near optimal solution. To reduce the complexity of such a PCB scheduling problem, this study develops a hierarchical approach which decomposes the original problem into two highly coupled sub-problems including job sequencing and lot scheduling with lot sizing, and further proposes a two-stage ant colony algorithm with lot sizing to evolve best results in the makespan performance. Extensive computational experiments have been conducted to illustrate the superiority of the algorithm in terms of computational time and stability.

Modeling and solving multi-skilled resource-constrained project scheduling problem with calendars in fuzzy condition

In this study, we aim to present a new model for the resource-constrained project scheduling problem (RCPSP) considering a working calendar for project members and determined the skill factor of any member using the efficiency concept. For this purpose, the recyclable resources are staff resources where any person with multiple skills can meet the required skills of activities in a given time. Then, considering uncertainty condition for parameters, it provided a fuzzy scheduling model and validated models by solving different examples. The proposed mathematical programming model optimizes the allocation of limited resources to project activities for scheduling purposes in an essential activity in the real condition of scheduling problems. Moreover, the proposed model can decrease the risk of deviation from scheduling by allocating members with higher skill factors to critical activities. Then, considering uncertainty condition for parameters, it provided a fuzzy scheduling model and validated models by solving different examples. Considering fuzzy conditions for the calendar of the project and multi-skill operators are firstly considered in this paper. Also, the recyclable resources are staff resources which are being considered for the model concurrently in response to the risks of availability to resources and delay in completing the project under uncertainty. The results derived from the model solved by CPLEX indicated a decreased need for employment and shortened project completion duration. Assuming the uncertainty of available resource capacity at any time, the results obtained from the fuzzy model for the value of objective function were evaluated under the influence of the resource calendar and showed the benefits. Effect of the multi-skill members with calendar constraints on the model is tested, and the advantages are determined.

Challenges to the use of research results by a former West African Economic and Monetary Union decision-maker.

The problem of the use of research results by public health decision-makers is a topical issue in developing countries, in which considerable research is conducted, but is poorly used.The author was previously Director of Health, Social Protection and Mutual Insurance of the UEMOA Commission from 2006 to 2017.The central question raised in this article is: What are the challenges to the use of research results by directors of public health programmes in a sub-regional integration institution?The main findings and challenges raised in this text can be summarized as follows:Programme and budget constraints surrounding the intervention planning process that prevent effective implementation of the health research results ;Implementation of programmes in member countries does not always comply with the guidelines adopted by the Union on the basis on good practice derived from research results;The dissemination of research results is insufficient due to calendar and budget constraints and certain prejudices concerning the efficacy of large-scale scientific meetings.

Mixed-integer linear programming and constraint programming formulations for solving resource availability cost problems

We consider the resource availability cost problem and two extensions through general temporal constraints and calendar constraints. With general temporal constraints minimum and maximum time lags between the activities can be ensured. Calendar constraints are used to model breaks in the availability of a resource, e.g., weekends or public holidays of resource types that equal staff. Especially if long-term and capital-intensive projects are under consideration, resource availability cost problems should be applied because in such projects it is more important to minimize the cost than, e.g., the project duration. We present mixed-integer linear programming (MILP) formulations as well as constraint programming (CP) models for the three problems. In a performance study we compare the results of the MILP formulations solved by cplex and the CP models solved by the lazy clause generation solver chuffed on benchmark instances from literature and also introduce new benchmarks. Our CP models close all open instances for resource availability cost problems from the literature.

Using constraint programming for solving RCPSP/max-cal

Resource-constrained project scheduling with the objective of minimizing project duration (RCPSP) is one of the most studied scheduling problems. In this paper we consider the RCPSP with general temporal constraints and calendar constraints. Calendar constraints make some resources unavailable on certain days in the scheduling period and force activity execution to be delayed while resources are unavailable. They arise in practice from, e.g., unavailabilities of staff during public holidays and weekends. The resulting problems are challenging optimization problems. We develop not only six different constraint programming (CP) models to tackle the problem, but also a specialized propagator for the cumulative resource constraints taking the calendar constraints into account. This propagator includes the ability to explain its inferences so it can be used in a lazy clause generation solver. We compare these models, and different search strategies on a challenging set of benchmarks using the lazy clause generation solver chuffed and IBM CPLEX CP Optimizer, respectively. We close all but 8 of the open problems of the benchmark set, extend the benchmark set by instances with up to 500 activities, and show that CP solutions are highly competitive with existing Mip models of the problem.

Scheduling rules to minimize total tardiness in a parallel machine problem with setup and calendar constraints

Quality control lead times are one of most significant causes of loss of time in the pharmaceutical and cosmetics industries. This is partly due to the organization of laboratories that feature parallel multipurpose machines for chromatographic analyses. The testing process requires long setup times and operators are needed to launch the process. The various controls are non-preemptive and are characterized by a release date, a due date and available routings. These quality processes lead to significant delays, and we therefore evaluate the total tardiness criterion. Previous heuristics were defined for the total tardiness criterion, parallel machines, and setup such as apparent tardiness cost (ATC) and ATC with setups (ATCS). We propose new rules and a simulated annealing procedure in order to minimize total tardiness.

Critical Path Scheduling under Resource Calendar Constraints

Resource calendars specify nonworking days of driving resources involved in construction projects. As part of the resource availability constraints in critical path method (CPM) scheduling, resource calendars may postpone activity start time, extend activity duration, and hence prolong the total project duration. Ultimately, resource calendars bring about changes to the critical path identification. Research has yet to address how to incorporate the effects of multiple resource calendars on the total float determination. In this research, the popular P3 software is used as a tool for investigating the current practice of CPM scheduling under resource limit and calendar constraints. We assess P3’s advanced resource scheduling functions (including resource leveling and resource calendars) and identify P3’s potential errors in total float determination. Further, we propose a new method based on the forward pass analysis alone for accurately evaluating activity total float subject to resource calendar constra...

Project scheduling with calendars

For many applications of project scheduling to real-life problems, it is necessary to take into account calendars specifying time intervals during which some resources such as manpower or machines are not available. Whereas the execution of certain activities like packaging may be suspended during breaks, other activities cannot be interrupted due to technical reasons. Minimum and maximum time lags between activities may depend on calendars, too. In this paper, we address the problem of scheduling the activities of a project subject to calendar constraints. We devise efficient algorithms for computing earliest and latest start and completion times of activities. Moreover, we sketch how to use these algorithms for developing priority-rule methods coping with renewable-resource constraints and calendars.