scholarly journals Exact Methods and Heuristics for Order Acceptance Scheduling Problem under Time-of-Use Costs and Carbon Emissions

2021 ◽  
Vol 11 (19) ◽  
pp. 8919
Author(s):  
Mariam Bouzid ◽  
Oussama Masmoudi ◽  
Alice Yalaoui
Keyword(s):  
Carbon Emissions ◽  
Optimization Problem ◽  
State Of The Art ◽  
Order Acceptance ◽  
Exact Methods ◽  
Solution Quality ◽  
Total Profit ◽  
Dependent Setup Times ◽  
Sequence Dependent Setup Times ◽  
Np Hardness

This research focuses on an Order Acceptance Scheduling (OAS) problem on a single machine under time-of-use (TOU) tariffs and taxed carbon emissions periods with the objective to maximize total profit minus tardiness penalties and environmental costs. Due to the NP-hardness of the considered problem especially in presence of sequence-dependent setup-times, two fix-and-relax (FR) heuristics based on different time-indexed (TI) formulations are proposed. A metaheuristic based on the Dynamic Island Model (DIM) framework is also employed to tackle this optimization problem. These approached methods show promising results both in terms of solution quality and solving time compared to state-of-the-art exact solving approaches.

scholarly journals Diversity Controlling Genetic Algorithm for Order Acceptance and Scheduling Problem

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Cheng Chen ◽  
Zhenyu Yang ◽  
Yuejin Tan ◽  
Renjie He
Keyword(s):  
Genetic Algorithm ◽  
Production Systems ◽  
Hamming Distance ◽  
Scheduling Problem ◽  
Order Acceptance ◽  
Solution Quality ◽  
Survival Selection ◽  
Benchmark Instances ◽  
Order Acceptance And Scheduling ◽  
Dependent Setup Times

Selection and scheduling are an important topic in production systems. To tackle the order acceptance and scheduling problem on a single machine with release dates, tardiness penalty, and sequence-dependent setup times, in this paper a diversity controlling genetic algorithm (DCGA) is proposed, in which a diversified population is maintained during the whole search process through survival selection considering both the fitness and the diversity of individuals. To measure the similarity between individuals, a modified Hamming distance without considering the unaccepted orders in the chromosome is adopted. The proposed DCGA was validated on 1500 benchmark instances with up to 100 orders. Compared with the state-of-the-art algorithms, the experimental results show that DCGA improves the solution quality obtained significantly, in terms of the deviation from upper bound.

scholarly journals A Multiobjective Optimization Approach to Solve a Parallel Machines Scheduling Problem

2010 ◽  
Vol 2010 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaohui Li ◽  
Lionel Amodeo ◽  
Farouk Yalaoui ◽  
Hicham Chehade
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Problem ◽  
Parallel Machines ◽  
Experimental Results ◽  
Optimization Approach ◽  
Due Dates ◽  
Nsga Ii ◽  
Parallel Machines Scheduling ◽  
Dependent Setup Times ◽  
Sequence Dependent Setup Times

A multiobjective optimization problem which focuses on parallel machines scheduling is considered. This problem consists of scheduling independent jobs on identical parallel machines with release dates, due dates, and sequence-dependent setup times. The preemption of jobs is forbidden. The aim is to minimize two different objectives: makespan and total tardiness. The contribution of this paper is to propose first a new mathematical model for this specific problem. Then, since this problem is NP hard in the strong sense, two well-known approximated methods, NSGA-II and SPEA-II, are adopted to solve it. Experimental results show the advantages of NSGA-II for the studied problem. An exact method is then applied to be compared with NSGA-II algorithm in order to prove the efficiency of the former. Experimental results show the advantages of NSGA-II for the studied problem. Computational experiments show that on all the tested instances, our NSGA-II algorithm was able to get the optimal solutions.

scholarly journals Cable tree wiring - benchmarking solvers on a real-world scheduling problem with a variety of precedence constraints

Constraints ◽  
2021 ◽  
Author(s):  
Jana Koehler ◽  
Josef Bürgler ◽  
Urs Fontana ◽  
Etienne Fux ◽  
Florian Herzog ◽  
...  
Keyword(s):  
State Of The Art ◽  
Precedence Constraints ◽  
Traveling Salesman ◽  
Mixed Integer ◽  
Automated Manufacturing ◽  
Scheduling Problem ◽  
Tasks Scheduling ◽  
Optimization Modulo Theories ◽  
Coupled Tasks ◽  
Np Hardness

AbstractCable trees are used in industrial products to transmit energy and information between different product parts. To this date, they are mostly assembled by humans and only few automated manufacturing solutions exist using complex robotic machines. For these machines, the wiring plan has to be translated into a wiring sequence of cable plugging operations to be followed by the machine. In this paper, we study and formalize the problem of deriving the optimal wiring sequence for a given layout of a cable tree. We summarize our investigations to model this cable tree wiring problem (CTW). as a traveling salesman problem with atomic, soft atomic, and disjunctive precedence constraints as well as tour-dependent edge costs such that it can be solved by state-of-the-art constraint programming (CP), Optimization Modulo Theories (OMT), and mixed-integer programming (MIP). solvers. It is further shown, how the CTW problem can be viewed as a soft version of the coupled tasks scheduling problem. We discuss various modeling variants for the problem, prove its NP-hardness, and empirically compare CP, OMT, and MIP solvers on a benchmark set of 278 instances. The complete benchmark set with all models and instance data is available on github and was included in the MiniZinc challenge 2020.

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