Minimizing sum of the due date assignment costs, maximum tardiness and distribution costs in a supply chain scheduling problem

Assarzadegan, Parisa; Rasti−Barzoki, Morteza

doi:10.1016/j.asoc.2016.06.005

Cited by 32 publications

(9 citation statements)

References 44 publications

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“…In Equation 4, A 1 represents a large enough number. Constraints (5) and (6) ensure that each order is served once, either by the manufacturer's fleet or by a third-party carrier through auction. Constraint (7) ensures the flow balance at each customer location.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…Few studies belong to this category [28,34]. Some studies tackled different variants of the standard production-transportation problem with routing delivery [16,23,25,38,41,62]; some studies focused on developing approaches for its solution [2,5,32,33,43]; and some studies incorporated additional features within the problem, such as multi-objective optimization [31], uncertainty and robustness [17,53], and financial planning [3].…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

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Integrating production scheduling and transportation procurement through combinatorial auctions

Triki

Piya

2020

Networks

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This study uses the winner determination problem (WDP) to integrate auction transportation procurement with decisions related to production scheduling. The basic problem arises when a manufacturer has to clear a combinatorial auction to decide whether to cover transportation needs by using the in‐house fleet or to procure transportation through auction. Thus, the manufacturer should include an additional decision level by integrating the WDP with production scheduling to gain efficiency and achieve savings in the logistics system. To the best of our knowledge, this is the first time production and transportation procurement problems are being solved simultaneously in an integrated manner. The study proposes a mathematical formulation and develops two heuristic approaches for solving the integrated problem. Extensive computational experiments and sensitivity analyses are reported to validate the model, assess the performance of the heuristics, and show the effect of integration on total cost.

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Section: Mathematical Modelmentioning

confidence: 99%

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Integrating production scheduling and transportation procurement through combinatorial auctions

Triki

Piya

2020

Networks

View full text Add to dashboard Cite

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“…The objective of the problem is to find jointly the optimal dispatch date for each job, the optimal location and size of the due window, and the optimal job sequence to minimize a cost function based on earliness, tardiness, holding time, window location, window size, and batch delivery. Assarzadegan and Rasti‐Barzoki () investigated the single‐machine batch delivery problem with common due date assignment and the objective is to minimize the sum of the maximum tardiness, due date assignment, and delivery costs. They developed an Adaptive Genetic algorithm and a Parallel Simulated Annealing algorithm to solve large‐scale instances of this

NP

‐hard problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated production, inventory, and batch delivery scheduling with due date assignment and two competing agents

Yin

Yong-jian

Wang

et al. 2018

Naval Research Logistics

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This paper considers several integrated production, inventory, and batch delivery scheduling problems on a single machine with due date assignment and two competing agents, each of which seeks to optimize its own performance. All the jobs of the first agent have a common due date, which is a decision variable to be determined by the decision maker, whereas the due dates of the jobs of the second agent are exogenously given. The jobs of the same agent are processed sequentially in batches and the batch processing time is equal to the total processing time of the jobs in the batch, where the batch size can be either bounded or unbounded. A batch is available only when all the jobs in it are completed. An available batch is delivered to its agent immediately, and the cost per batch delivery is fixed and independent of the number of jobs in the batch. Finished jobs are kept in inventory, if necessary, incurring an additional holding cost. The first agent wishes to find a job sequence, a common due date, and a dispatch date for each of its jobs that jointly minimize the total cost comprising the earliness, weighted number of tardy jobs, job holding, due date assignment, and batch delivery costs, while the second agent seeks to minimize one of the following criteria plus the batch delivery cost: the maximum value of a regular scheduling criterion, total completion time, and weighted number of tardy jobs. The overall objective is to minimize the objective value of the first agent, subject to the objective value of the second agent not exceeding a given threshold. For each of the problems considered, we study its computational complexity and develop exact and/or approximation solution algorithms.

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“…They present a two-stage biobjective mixed integer stochastic programming model for providing strategic and tactical decisions, respectively, in the first and second stages to minimize costs and also the negative impact.Özceylan et al [20] develop a mixed integer nonlinear programming (MINLP) model, which optimizes the tactical decisions on balancing the decomposition lines in the reverse supply chain and the strategic decisions related to the quantity of Mathematical Problems in Engineering 3 (Table 1). However, recently other researchers have investigated this problem meticulously (e.g., [22,23]). Table 1 summarizes similar works and highlights our contribution in this study.…”

Section: Literature Reviewmentioning

confidence: 99%

A Modified Priority-Based Encoding for Design of a Closed-Loop Supply Chain Network Using a Discrete League Championship Algorithm

Ghahremani-Nahr

Kian

Rezazadeh

2018

Mathematical Problems in Engineering

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In a closed-loop supply chain network, the aim is to ensure a smooth flow of materials and attaining the maximum value from returning and end-of-life goods. This paper presents a single-objective deterministic mixed integer linear programming (MILP) model for the closed-loop supply chain (CLSC) network design problem consisting of plants, collection centers, disposal centers, and customer zones. Our model minimizes the total costs comprising fixed opening cost of plants, collection, disposal centers, and transportation costs of products among the nodes. As supply chain network design problems belong to the class of NP-hard problems, a novel league championship algorithm (LCA) with a modified priority-based encoding is applied to find a near-optimal solution. New operators are defined for the LCA to search the discrete space. Numerical comparison of our proposed encoding with the existing approaches in the literature is indicative of the high quality performance of the proposed encoding.

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Minimizing sum of the due date assignment costs, maximum tardiness and distribution costs in a supply chain scheduling problem

Cited by 32 publications

References 44 publications

Integrating production scheduling and transportation procurement through combinatorial auctions

Integrating production scheduling and transportation procurement through combinatorial auctions

Integrated production, inventory, and batch delivery scheduling with due date assignment and two competing agents

A Modified Priority-Based Encoding for Design of a Closed-Loop Supply Chain Network Using a Discrete League Championship Algorithm

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