The concrete delivery problem

From an operational point of view, Ready-Mixed Concrete Suppliers are faced with challenging operational problems such as the acquisition of raw materials, scheduling of production facilities, and the transportation of concrete. This paper is centered around the logistical and distributional part of...

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Published in:	Computers & operations research Vol. 48; pp. 53 - 68
Main Authors:	Kinable, J., Wauters, T., Vanden Berghe, G.
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier Ltd 01.08.2014 Elsevier Pergamon Press Inc
Subjects:	Applied sciences Computer simulation Concrete Concretes Constraint Programming Deliveries Delivery scheduling Exact sciences and technology Exact solutions Heuristic Integer programming Logistics Mathematical models Mathematical problems Mathematical programming Meta-heuristics Mixed Integer Programming Operational research and scientific management Operational research. Management science Operations research Production scheduling Scheduling Scheduling, sequencing Studies Vehicle routing Scheduling Mixed Integer Programming Constraint Programming Vehicle routing Meta-heuristics Lower bound Fleet Vehicle routing problem Mixed integer programming Routing Raw materials Modeling Bounded solution Constrained optimization Exact solution Production management Building site Concrete construction Heuristic method Ready mixed concrete Metamodel Logistics
ISSN:	0305-0548, 1873-765X, 0305-0548
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Abstract	From an operational point of view, Ready-Mixed Concrete Suppliers are faced with challenging operational problems such as the acquisition of raw materials, scheduling of production facilities, and the transportation of concrete. This paper is centered around the logistical and distributional part of the operation: the scheduling and routing of concrete, commonly known as the Concrete Delivery Problem (CDP). The problem aims at finding efficient routes for a fleet of (heterogeneous) vehicles, alternating between concrete production centers and construction sites, and adhering to strict scheduling and routing constraints. Thus far, a variety of CDPs and solution approaches have appeared in academic research. However, variations in problem definitions and the lack of publicly available benchmark data inhibit a mutual comparison of these approaches. Therefore, this work presents a more fundamental version of CDP, while preserving the main characteristics of the existing problem variations. Both exact and heuristic algorithms for CDP are proposed. The exact solution approaches include a Mixed Integer Programming (MIP) model and a Constraint Programming model. Similarly, two heuristics are studied: the first heuristic relies on an efficient best-fit scheduling procedure, whereas the second heuristic utilizes the MIP model to improve delivery schedules locally. Computational experiments are conducted on new, publicly accessible, data sets; results are compared against lower bounds on the optimal solutions.
AbstractList	From an operational point of view, Ready-Mixed Concrete Suppliers are faced with challenging operational problems such as the acquisition of raw materials, scheduling of production facilities, and the transportation of concrete. This paper is centered around the logistical and distributional part of the operation: the scheduling and routing of concrete, commonly known as the Concrete Delivery Problem (CDP). The problem aims at finding efficient routes for a fleet of (heterogeneous) vehicles, alternating between concrete production centers and construction sites, and adhering to strict scheduling and routing constraints. Thus far, a variety of CDPs and solution approaches have appeared in academic research. However, variations in problem definitions and the lack of publicly available benchmark data inhibit a mutual comparison of these approaches. Therefore, this work presents a more fundamental version of CDP, while preserving the main characteristics of the existing problem variations. Both exact and heuristic algorithms for CDP are proposed. The exact solution approaches include a Mixed Integer Programming (MIP) model and a Constraint Programming model. Similarly, two heuristics are studied: the first heuristic relies on an efficient best-fit scheduling procedure, whereas the second heuristic utilizes the MIP model to improve delivery schedules locally. Computational experiments are conducted on new, publicly accessible, data sets; results are compared against lower bounds on the optimal solutions. From an operational point of view, Ready-Mixed Concrete Suppliers are faced with challenging operational problems such as the acquisition of raw materials, scheduling of production facilities, and the transportation of concrete. This paper is centered around the logistical and distributional part of the operation: the scheduling and routing of concrete, commonly known as the Concrete Delivery Problem (CDP). The problem aims at finding efficient routes for a fleet of (heterogeneous) vehicles, alternating between concrete production centers and construction sites, and adhering to strict scheduling and routing constraints. Thus far, a variety of CDPs and solution approaches have appeared in academic research. However, variations in problem definitions and the lack of publicly available benchmark data inhibit a mutual comparison of these approaches. Therefore, this work presents a more fundamental version of CDP, while preserving the main characteristics of the existing problem variations. Both exact and heuristic algorithms for CDP are proposed. The exact solution approaches include a Mixed Integer Programming (MIP) model and a Constraint Programming model. Similarly, two heuristics are studied: the first heuristic relies on an efficient best-fit scheduling procedure, whereas the second heuristic utilizes the MIP model to improve delivery schedules locally. Computational experiments are conducted on new, publicly accessible, data sets; results are compared against lower bounds on the optimal solutions. [PUBLICATION ABSTRACT]
Author	Kinable, J. Wauters, T. Vanden Berghe, G.
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Keywords	Scheduling Mixed Integer Programming Constraint Programming Vehicle routing Meta-heuristics Lower bound Fleet Vehicle routing problem Mixed integer programming Routing Raw materials Modeling Bounded solution Constrained optimization Exact solution Production management Building site Concrete construction Heuristic method Ready mixed concrete Metamodel Logistics
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SubjectTerms	Applied sciences Computer simulation Concrete Concretes Constraint Programming Deliveries Delivery scheduling Exact sciences and technology Exact solutions Heuristic Integer programming Logistics Mathematical models Mathematical problems Mathematical programming Meta-heuristics Mixed Integer Programming Operational research and scientific management Operational research. Management science Operations research Production scheduling Scheduling Scheduling, sequencing Studies Vehicle routing
Title	The concrete delivery problem
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